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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Evaluating Enhanced Reservoir Evaporation Losses From CMIP6‐Based Future Projections in the Contiguous United States

Abstract Enhanced reservoir evaporation has become an emerging concern regarding water loss, especially when compounded with the ever‐increasing water demand. In this study, we evaluated the evaporation rates and losses for 678 major reservoirs (representing nearly 90% of total storage capacity) in the Contiguous United States over historical baseline (1980–2019), near‐term (2020–2039), and mid‐term (2040–2059) future periods. The evaporation rate was estimated using the Lake Evaporation Model (LEM), an advanced lake evaporation model that addresses both heat storage and fetch effects, driven by multi‐ensemble downscaled Coupled Model Intercomparison Projects 6 (CMIP6) projections under the SSP585 emission scenario. The results project that the evaporation loss may increase by 2.5 × 10 7 m 3 /yr through the research period (1980–2059). Among all regions, the Rio Grande is projected to have the largest increasing rate in the near‐term and mid‐term future, with values of 7.11% of 10.25%, respectively. At the seasonal scale, the most significant increase in the evaporation rate is projected during the fall. The evaporation is projected to increase faster than the streamflow over many of the regions in the southwestern US during the summer/fall, suggesting that the shortage of water will be further exacerbated. The climate models contribute the most to the variance, as compared to the other components related to the projection of evaporation losses (e.g., hydrological model, downscaling method, and historical meteorological data set). These findings demonstrate the need to consider accelerated water loss through open water evaporation in long‐term water resources planning across various spatiotemporal scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Xanthos-Lake Model Source Code

This repository contains the source code for Xanthos-Lake, a lake-modeling extension of the Xanthos framework that introduces a coupled lake component comprising the Xanthos-Lake Snow and Ice Model (xLSIM) and the Xanthos-Lake Water Balance Model (xLWBM). xLSIM is a basin-aware machine-learning model for lake snow, ice, and thermal conditions. It predicts monthly lake ice thickness, snow depth, snow-cover fraction, mixing-layer temperature, and lake ice fraction from meteorological forcing and lake surface-area information. It uses sequence-based deep-learning architectures, including Transformer and hybrid Long Short-Term Memory–Transformer (LSTM–Transformer) models, together with seasonal encoding, multi-lake learning, physical masking, and basin-level cryospheric and non-cryospheric classification. The training workflow uses Ray for scalable execution and includes optional Ray Tune hyperparameter optimization. Model predictions, observations, diagnostics, and feature-importance outputs are written in NetCDF. xLWBM is the water-balance component of the new lake framework. It simulates monthly lake storage, surface area, evaporation, inflow, outflow, and lake–groundwater exchange. It combines physical water-balance equations with calibrated bathymetric relationships, weir-based outlet flow, modified Penman open-water evaporation, groundwater head relaxation, Penman–Monteith snow and ice sublimation, and snow, ice, and thermal conditions supplied by xLSIM. The model calibrates lake parameters against satellite-derived surface-area data, using evaporation-based calibration where surface-area data are unavailable, and supports small, medium, and large lake classes. For large lakes, xLWBM is integrated with the managed-routing workflow so that lake storage and outflow interact directly with downstream river routing and reservoir operations. Together, xLSIM and xLWBM provide Xanthos with a coupled lake-modeling capability. xLSIM supplies the snow, ice, and thermal conditions that affect lake evaporation and snow- and ice-related water exchanges, while xLWBM translates those conditions into dynamic lake storage, surface area, evaporation, and discharge. In return, xLWBM supplies evolving lake surface area to xLSIM. This coupling enables Xanthos to represent lakes as active hydrologic components within basin-scale water-availability and routing simulations.

Machine Learning↗
DOE OSTI2024

Impact of Floating PV (FPV) System on Water Evaporation: Case Study of an Open Loop Reservoir in North Carolina

Fresh water scarcity is becoming one of the important concerns worldwide. This situation of water scarcity is further exacerbated by the increase in water evaporation due to climate change. This manuscript will address this concern by considering the impact of floating photovoltaics (FPVs) systems on water evaporation. The installation of PV modules on the water bodies can help reduce the water evaporation rate from reservoirs by reducing the evaporating area of the water surface. This work evaluates the effect of FPV on water evaporation rates in the TuckerTown reservoir located in North Carolina state of United States. Meteorological data, such as mean temperature and dew-point, are used to calculate the rate of the water evaporation by Linacre method. The simulation results for the TuckerTown case study showed that the aggregated avoided evaporated volume for one year is 9 million gallons.

14 SOLAR ENERGY↗
DOE OSTI2023

Estimating Future Surface Water Availability Through an Integrated Climate‐Hydrology‐Management Modeling Framework at a Basin Scale Under CMIP6 Scenarios

Abstract Climate change and increasing water demand due to population growth pose serious threats to surface water availability. The biggest challenge in addressing these threats is the gap between climate science and water management practices. Local water planning often lacks the integration of climate change information, especially with regard to its impacts on surface water storage and evaporation as well as the associated uncertainties. Using Texas as an example, state and regional water planning relies on the use of reservoir “Firm Yield” (FY)—an important metric that quantifies surface water availability. However, this existing planning methodology does not account for the impacts of climate change on future inflows and on reservoir evaporation. To bridge this knowledge gap, an integrated climate‐hydrology‐management (CHM) modeling framework was developed, which is generally applicable to river basins with geographical, hydrological, and water right settings similar to those in Texas. The framework leverages the advantages of two modeling approaches—the Distributed Hydrology Soil Vegetation Model (DHSVM) and Water Availability Modeling (WAM). Additionally, the Double Bias Correction Constructed Analogues method is utilized to downscale and incorporate Coupled Model Intercomparison Project Phase 6 GCMs. Finally, the DHSVM simulated naturalized streamflow and reservoir evaporation rate are input to WAM to simulate reservoir FY. A new term—“Ratio of Firm Yield” (RFY)—is created to compare how much FY changes under different climate scenarios. The results indicate that climate change has a significant impact on surface water availability by increasing reservoir evaporation, altering the seasonal pattern of naturalized streamflow, and reducing FY.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Theory of the photomolecular effect

It is well-known that water in liquid and vapor phases exhibits weak visible-light absorption. Recent experiments, however, show that at the liquid-air interface, absorption drastically increases, accelerating evaporation beyond thermal limits by 2–5 times. Strikingly, evaporation peaks at green wavelengths, despite no corresponding absorptance peak. The underlying mechanism of this observation, termed the photomolecular effect, remains puzzling, particularly as water molecules do not exhibit resonance peaks in the visible spectrum. Here, we present a theoretical model explaining the effect. We show that surface-bound water clusters undergo non-resonant photon-driven evaporation, with green light being particularly effective. Crucially, we do not expect green light to couple more strongly than other wavelengths to the molecules at the surface, rather the energy of green light is more effectively used to vaporize water. Our model accounts for why the evaporation peak does not align with absorptance and provides a quantum mechanical explanation of how a single photon can vaporize an entire molecular cluster. This model challenges conventional views on water-light interactions, revealing a fundamentally non-thermal evaporation mechanism. Furthermore, our findings have implications for water purification, energy-efficient drying, and climate modeling, opening new pathways for optimizing evaporation-based technologies.

Interfacial evaporation↗
DOE OSTI2022

Evaporation of Water Nanodroplets on Heated Surfaces: Does Nano Matter?

While experiments and continuum models have provided a relatively good understanding of the evaporation of macroscopic water droplets, elucidating how sessile nanodroplets evaporate is an open question critical for advancing nanotechnological applications where nanodroplets can play an essential role. In this study, using molecular dynamics simulations, we find that evaporating nanodroplets, in contrast to their macroscopic counterparts, are not always in thermal equilibrium with the substrate and that the vapor concentration on the nanodroplet surface does not reach a steady state. As a result, the evaporative behavior of nanodroplets is significantly different. Regardless of hydrophobicity, nanodroplets do not follow conventional evaporation modes but instead exhibit dynamic wetting behavior characterized by huge, non-equilibrium, isovolumetric fluctuations in the contact angle and contact radius. For hydrophilic nanodroplets, the evaporation rate, controlled by the vapor concentration, decays exponentially over time. Hydrophobic nanodroplets follow stretched exponential kinetics arising from the slower thermalization with the substrate. The evaporative half-lifetime of the nanodroplets is directly related to the thermalization time scale and therefore increases monotonically with the hydrophobicity of the substrate. Finally, the evaporative flux profile along the nanodroplet surface is highly nonuniform but does not diverge at the contact line as the macroscopic continuum models predict.

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

Universal correlation for falling film evaporation heat transfer coefficients of water and seawater

Horizontal falling film evaporators are widely utilized in desalination industries to increase fresh water supply. However, universal correlations for seawater falling film evaporation under varied operational and geometrical conditions are simply unavailable in open literature. Thus, this study aims to develop such a universal correlation for both plain and enhanced tubes. The detailed heat transfer mechanisms are reviewed, and rational parameters are incorporated to develop the universal correlation. A dataset of 994 data points from 9 sources covering a wide range of conditions was compiled. These conditions include Reynolds numbers from 10 to 7235, heat fluxes from 7.7 to 208 kW/m -2 , saturation temperatures from 278 to 401 K, salinities from 0 to 60 gsalt kg -1 water, tube diameters from 15.8 to 50.8 mm, and liquid feeder height to diameter ratios from 1 to 2.25. Upon analysis, it was found that most of the recommended existing correlations exhibited poor predictive accuracy, as evidenced by larger MADs. The developed correlation in this study demonstrated the best predictive accuracy for the entire dataset, yielding a MAD of 16.8 % and an R 2 of 0.82. Furthermore, the performance of the new correlation was individually assessed across a broader spectrum of operational and design conditions, reflecting the individual conditions’ influences with an overall MAD of 20 %.

42 ENGINEERING↗
DOE OSTI2025

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory Protected Areas Database of the United States (PAD-US) areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗
DOE OSTI2026

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway or within an airport area boundary Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory USGS Protected Areas Database of the United States (PAD-US) GAP status 1, 2, or 3 areas US National Parks Wetlands USFWS critical habitats BIA land areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗
DOE OSTI2025

Cooperative Role of Mixed Solvent in the Evaporation-Induced Self-Assembly of Polypeptoid Nanocrystals

Peptoids, or polypeptoids, are biomimetic polymers that can self-assemble into nanocrystals for biomedical and biotechnological applications. Polypeptoid nanocrystals can be prepared by evaporation-induced self-assembly, but the roles of solvent components for this process have long been overlooked at the molecular level, leaving a tunable parameter for improving self-assembly protocols. This work utilized molecular dynamics simulations to study the effects of water and the commonly used tetrahydrofuran (THF) on the assembly of nanosheets from molecules of acetylated diblock polypeptoid, poly-(N-decylglycine)-b-poly-(N-2-(2-(2-methoxyethoxy)-ethoxy) ethylglycine), abbreviated as Ac-Ndc10-Nte10. To probe the stages of self-assembly, isolated molecules and preassembled nanofibers/nanosheets were simulated in pure THF, water, and their mixtures, respectively. The assembly energies show that the THF/water mixture has a greater tendency to form nanosheets than pure water. In a THF/water mixture, polypeptoids were found more uncoiled in isolated states, less compact in disordered agglomerates, and with reduced requirement for the Nte block to cover hydrophobic Ndc surfaces in the nanocrystals. Mixed solvent is vital to initiating self-assembly, as THF assists in the opening of coiled polypeptoid molecules, while water provides the thermodynamics to aggregate and ultimately form nanocrystals. To obtain wider nanosheets, it is recommended that some THF be maintained in the aqueous solvent before it becomes exhausted by evaporation. Near the nanosheet surface, the THF concentration is higher than that in bulk solution (3-4 times in 4 M THF/water). The strong adsorption of THF indicates the self-assembly in a de facto mixed solvent. These results are expected to guide the refinement of evaporation-induced self-assembly protocols for polypeptoid nanocrystals.

Luo, Xubo↗
DOE OSTI2020

Kinetics of TATB and LX-17 Decomposition by Thermal Analysis

The kinetics of TATB decomposition have been investigated by thermal analysis (thermogravimetric analysis, TGA, and differential scanning calorimetry, DSC) at both LLNL and the University of Alabama Birmingham. This report summarizes progress in understanding from those results within the context of identifying the global reaction mechanism, i.e., sequential, autocatalytic, competitive, or some mixture thereof. A particularly important issue is how pressure affects both the reaction rate and enthalpy. The effect of pressure helps identify dominant mechanisms and construct and constrain a global mechanism that will work over a wide range of conditions. This memorandum is simply a snapshot of current progress and not a definitive interpretation. I have written it to organize work of others and my interpretations in a systematic manner with the intention of stimulating further advances in understanding. SDT data comes from Jen Montgomery at LLNL, and high-pressure DSC comes from Victoria Stanford and Sergey Vyazovkin at University of Alabama at Birmingham. Major observations and conclusions, some new and some not, are (1) outgassing below 150 °C prior to decomposition releases adsorbed water vapor, (2) outgassing between 150 and 250 °C may come primarily from intercalated water (3) initial thermal decomposition above 250 °C or so involves dehydration of TATB to create furazans, (4) quickly heating to higher temperatures in open pans with flowing gas leads primarily to TATB evaporation between 270 and 390 °C, (5) using a pinhole crucible at atmospheric pressure largely eliminates TATB sublimation, (6) at typical thermal analysis heat rates, the main stage of decomposition is described by a single mass loss process, and decomposition of residual material is spread over a wide range of thermal severity, (7) at typical thermal analysis heat rates and constant temperatures above 300 °C, heat release occurs in two overlapping peaks, with the first one a little faster than mass loss and the second on a little slower than mass loss, (8) total heat release increases significantly with heating rate and substantially with increased pressure, and (9) isothermal experiments at 340 °C indicate that the first exotherm increases by more with LX-17 than TATB, which suggests a possible chemical role of Kel-F decomposition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

IOTA Pre-Bake Test Development

The poster presentation prepared for the IOTA (Integrable Optics Test Accelerator) Pre-Bake Test Development project consists of introducing the background of the project, the work completed, and the new test configurations available with the newly designed assembly. It explains the scale of the projects, both within the IOTA ring assembly and test assembly, and describes the purpose in baking or incrementing and holding exterior heat on the beampipe to reduce impurities in the vacuum. The originally designed test, Configuration One, uses RCA scans on the interior of the pipe, increments and holds heat for a set amount of time, and is scanned again to check for water evaporation. Configuration Two begins with the same test for Configuration One but has a second cross section of beampipe separated by a gate valve. After configuration one is complete, the gate valve opens, and after a period of cooling the other side is heated, molecular movement is scanned and observed.

Seagrave, Kayla [DuPage Coll.]↗
DOE OSTI2024

Ice-slurry production for solar-ice systems using supercooling with an in-stream crystallizer

Using ice slurry produced from supercooled water with an in-stream crystallizer opens a new path for solarice systems, increasing efficiency and reducing investment cost compared to ice-on-coil systems. Power needs are decoupled from the stored energy since the heat exchangers are not evenly distributed in the ice storage vessel but directly placed as the heat pump evaporator, which depends on the heat pump capacity and not on the ice storage volume. The novel ice storage design can serve as a heat source for a heat pump, where its evaporator is used to supercool water below 0 °C, or for refrigeration. The supercooled water at a temperature around −2 °C, maintained in a meta-stable liquid state, is triggered to nucleate in an in-stream crystallizer. The current design of the ice crystallizer allows for continuous operation of the system and scalability. Experimental results obtained with a gasketed plate heat exchanger used to supercool water and an in-stream crystallizer operated at a power of up to 6.5 kW are presented.

Thamm, Ann-Katrin↗
DOE OSTI2026

Accelerated Carbon and Water Cycles in the Amazon and Congo Basins Revealed From TRENDY Models and Remote Sensing Products

Tropical forests play a vital role in the global carbon cycle and land–atmosphere interactions. Estimating tropical forest carbon–water dynamics is challenging due to observational and modeling uncertainties. This study leverages the “Trends and drivers of the regional scale terrestrial sources and sinks of carbon dioxide” (TRENDY) project models and satellite observations to assess changes (2003–2021) in vegetation carbon, gross primary production (GPP), evapotranspiration (ET), and net biosphere production (NBP) in the Amazon and Congo. Atmospheric CO 2 , climate variability, and land use and land cover changes constrain these variables between 1700 and 2021 with the overall increasing trends of carbon stock and fluxes. The models overestimate vegetation carbon and GPP, while ET and NBP are consistent with observations. Fire-activated models predict lower values for vegetation carbon and GPP, ET, and NBP, aligning more closely with observations. The higher ET from fire-activated models may result from enhanced soil evaporation due to increased canopy openings. Fire-inactivated models could well estimate the magnitudes of NBP. The high vegetation carbon in nitrogen-enabled models points to simulation uncertainties and imbalance in model numbers regarding the nitrogen cycle. Although the nitrogen cycle enhances water use efficiency in both the Amazon and Congo, the models show a higher sensitivity to the nitrogen cycle in the Congo. This study highlights the challenges in accurately representing tropical biogeochemical cycles and the values of satellite products in model evaluations, underscoring the need for standard modeling protocols that address biogeochemical components (e.g., nutrient cycles) to better resolve process-based representations.

Shi, Mingjie [Pacific Northwest National Laborator↗
DOE OSTI2020

Dynamic domain kinematic modelling for predicting interflow over leaky impeding layers

Traditional Boussinesq or kinematic simulations of interflow (i.e., lateral subsurface flow) assume no leakage through the impeding layer and require a no-flow boundary condition at the ridge top. However, recent analyses of many interflow-producing landscapes indicate that leaky impeding layers are common, that most interflow percolates well before reaching the toe slope, and therefore, the downslope contributing length is shorter than the hillslope length. In watersheds characterised by perched interflow over a low conductivity layer through permeable topsoil, interflow with percolation may be modelled with a kinematic wave model using a mobile upslope boundary condition defining the hillslope portion contributing interflow to valleys. Here, we developed and applied a dynamic interflow model to simulate interflow using a downslope travel distance concept such that only the active contributing length is modelled at any time. The model defines a variable active area based on the depth of the perched layer, the topographic slope and the ratio of the hydraulic conductivity of topsoil to that of the impeding layer. It incorporates a two-layer soil moisture accounting water balance analysis, a pedo-transfer function, and percolation and evaporation routines to predict interflow rates in continuous and event-based scenarios. We tested the modelling concept on two sets of data (2-year dataset of rainfall observations for the continuous simulation and a multi-day irrigation experiment for the event simulation) from a 121-m-long open interflow collection trench on an experimental hillslope at the Savannah River Site, South Carolina. The continuous model simulation partially represented the observed interflow hydrograph and perched water depth in the experimental hillslope with correlation coefficients of 0.85 and 0.35, respectively. Model performance improved significantly at event-scale analysis. The modelling approach realistically represents interflow dynamics in hillslopes with leaky impeding layers and can be integrated into catchment-scale hydrology models for more detailed hillslope process modelling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Daily evapotranspiration changes during heatwaves at 32 NEON sites, 2019-2021

This dataset provides partitioned evapotranspiration (ET, the combined loss of water from soil and plant surfaces) anomalies during heatwave events—soil evaporation (E) and transpiration (T)—for 268 heatwave events across 32 National Ecological Observatory Network (NEON) flux sites in the contiguous United States from 2019–2021. Using an ensemble of four high-frequency turbulence methods (Flux-variance Similarity, Conditional Eddy Covariance [CEC], CEC with Water-Use Efficiency, and Conditional Eddy Accumulation; see Zahn and Bou-Zeid 2024), half-hourly transpiration-to-evapotranspiration (T/ET) ratios were derived from 20 hertz (Hz, cycles per second) eddy covariance measurements of carbon dioxide (CO₂) and water vapor (H₂O) concentrations. The dataset spans six vegetation types including evergreen and deciduous forests, grasslands, cultivated crops, shrublands, and emergent herbaceous wetlands. Data Package Contents: The dataset includes a single CSV (comma-separated values) file containing daily anomalies (deviations from baseline conditions) for transpiration (Delta_T), evaporation (Delta_E), total evapotranspiration (Delta_ET), and T/ET ratio (Delta_T_ET) during each day of identified heatwave events. The file also includes site codes, dates, heatwave event identifiers, and day-of-heatwave indicators. The CSV file can be opened with spreadsheet software (Microsoft Excel, Google Sheets) or programming environments (Python, R, MATLAB). This resource enables researchers to investigate ecosystem-specific responses to thermal extremes, validate land surface model partitioning of ET fluxes, and examine feedbacks between water cycling and surface energy balance during heatwaves. The dataset is particularly valuable for studies linking vegetation hydraulic strategies to climate resilience, as it captures the divergent responses of shallow-rooted versus deep-rooted ecosystems. Potential applications include improving drought early warning systems, informing irrigation management strategies, and advancing our mechanistic understanding of land-atmosphere interactions under extreme heat conditions.

Day of Heatwave↗
DOE OSTI2021

A stable isotope record of late Quaternary hydrologic change in the northwestern Brooks Range, Alaska (eastern Beringia)

A submillennial-resolution record of lake water oxygen isotope composition (δ 18 O) from chironomid head capsules is presented from Burial Lake, northwest Alaska. The record spans the Last Glacial Maximum (LGM; ~20–16k cal a bp) to the present and shows a series of large lake δ 18 O shifts (~5‰). Relatively low δ 18 O values occurred during a period covering the LGM, when the lake was a shallow, closed-basin pond. Higher values characterize deglaciation (~16–11.5k cal a Bp) when the lake was still closed but lake levels were higher. A rapid decline between ~11 and 10.5k cal a Bp indicates that lake levels rose to overflowing. Lake δ 18 O values are interpreted to reflect the combined effects of changes in lake hydrology, growing season temperature and meteoric source water as well as large-scale environmental changes impacting this site, including opening of the Bering Strait and shifts in atmospheric circulation patterns related to ice-sheet dynamics. The results indicate significant shifts in precipitation minus evaporation across the late Pleistocene to early Holocene transition, which are consistent with temporal patterns of vegetation change and paludification. This study provides new perspectives on the paleohydrology of eastern Beringia concomitant with human migration and major turnover in megafaunal assemblages.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Effects of Wind Shear and Aerosol Conditions on the Organization of Precipitating Marine Stratocumulus Clouds

Here this study examines how wind shear affects precipitating marine stratocumulus clouds under different cloud droplet number concentrations (N d ). We performed a series of large eddy simulations (LES) of nocturnal marine stratocumulus clouds using Cloud Model 1 (CM1). The simulations show that N d is the dominant factor for cloud cellular organization in this cloud regime rather than wind shear. Low N d characterizes the open cellular structure with a high in-cloud liquid water path (LWP). When wind shear is increased, the cloud fraction tends to decrease along with LWP, suggesting the cloud top region is significantly influenced by the entrainment and mixing of dry air from the free troposphere. We also examine cold pools in open and closed cellular clouds. Open-cell clouds produce larger and deeper cold pools compared to closed-cell clouds. Interestingly, cold pools can exist without surface precipitation and are produced by evaporation of light precipitation (drizzle) below the cloud base with weak downdrafts. The evaporation of raindrops and drizzle play an important role in initiating new convection, particularly where colliding outflows occur downstream of the cloud. This secondary convection contributes to the development and maintenance of the cloud cellular organization and formation.

54 ENVIRONMENTAL SCIENCES↗