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At least 127 records · Page 7

Improvements to CTF for Modeling of Boiling Water Reactor Geometry and Operating Conditions

This report documents work done to improve CTF modeling of boiling water reactor (BWR) designs during FY 2020. Several improvements were made to the geometry modeling capabilities, including adding support for modeling of inlet flow orifices, axially varying large water rods, channel boxes with large corner round radii, and quarter symmetry models. Work was also done to improve on the numerical stability and run-time performance of CTF in Virtual Environment for Reactor Applications (VERA) for core-scale BWR problems. An outer iteration loop was implemented that ensures mass and energy are conserved before moving on to the next time step in the solution. The ability to use a direct solver for the pressure matrix was also added, which reduces the matrix solution error and improves code stability and run-time performance. Improvements to the pressure balance iteration loop were needed to allow CTF to be used in a coupled VERA solution of a model of Hatch that was developed. Finally, various improvements have led to a 2×reduction in the total VERA walltime for the Hatch model.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Learning intermolecular forces at liquid–vapor interfaces

By adopting a perspective informed by contemporary liquid-state theory, we consider how to train an artificial neural network potential to describe inhomogeneous, disordered systems. Here, we find that neural network potentials based on local representations of atomic environments are capable of describing some properties of liquid-vapor interfaces but typically fail for properties that depend on unbalanced long-ranged interactions that build up in the presence of broken translation symmetry. These same interactions cancel in the translationally invariant bulk, allowing local neural network potentials to describe bulk properties correctly. By incorporating explicit models of the slowly varying long-ranged interactions and training neural networks only on the short-ranged components, we can arrive at potentials that robustly recover interfacial properties. We find that local neural network models can sometimes approximate a local molecular field potential to correct for the truncated interactions, but this behavior is variable and hard to learn. Generally, we find that models with explicit electrostatics are easier to train and have higher accuracy. We demonstrate this perspective in a simple model of an asymmetric dipolar fluid, where the exact long-ranged interaction is known, and in an ab initio water model, where it is approximated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

General circulation models simulate negative liquid water path–droplet number correlations, but anthropogenic aerosols still increase simulated liquid water path

General circulation models' (GCMs) estimates of the liquid water path adjustment to anthropogenic aerosol emissions differ in sign from other lines of evidence. This reduces confidence in estimates of the effective radiative forcing of the climate by aerosol–cloud interactions (ERFaci). The discrepancy is thought to stem in part from GCMs' inability to represent the turbulence–microphysics interactions in cloud-top entrainment, a mechanism that leads to a reduction in liquid water in response to an anthropogenic increase in aerosols. In the real atmosphere, enhanced cloud-top entrainment is thought to be the dominant adjustment mechanism for liquid water path, weakening the overall ERFaci. We show that the latest generation of GCMs includes models that produce a negative correlation between the present-day cloud droplet number and liquid water path, a key piece of observational evidence supporting liquid water path reduction by anthropogenic aerosols and one that earlier-generation GCMs could not reproduce. However, even in GCMs with this negative correlation, the increase in anthropogenic aerosols from preindustrial to present-day values still leads to an increase in the simulated liquid water path due to the parameterized precipitation suppression mechanism. This adds to the evidence that correlations in the present-day climate are not necessarily causal. We investigate sources of confounding to explain the noncausal correlation between liquid water path and droplet number. These results are a reminder that assessments of climate parameters based on multiple lines of evidence must carefully consider the complementary strengths of different lines when the lines disagree.

54 ENVIRONMENTAL SCIENCES↗

Groundwater and Surface Water Flow (GSFLOW) model files to explore bedrock circulation depth and porosity in Copper Creek, Colorado

This data package contains integrated hydrological model input and output files for Copper Creek, Colorado (24 km2), a tributary of the East River located in the headwaters of the Upper Colorado River Basin. The model code is the U.S. Geological Survey (USGS) Groundwater and Surface Water Flow (GSFLOW) model. The model contains a 100-m grid resolution and a daily timestep. The land surface model is dynamically linked to a three-dimensional groundwater flow model that allows for streamflow gaining and losing conditions. The groundwater model contains 12 model layers and extends 400 m below land surface. The original Copper Creek model was modified to contain geologic layers representing saprolite, shallow bedrock, and deep bedrock. Endmember depth versus hydraulic conductivity relationships and porosity values for fractured crystalline rock are simulated. For the shallow case, median flow depths occur in the shallow saprolite at depths <8 m, while the deep case promotes a median groundwater flow depth of 100 m. With this modeling framework we compare streamflow response to a plausible worst-case drought lasting up to five years. Streamflow metrics of analysis include average streamflow, fraction of stream network that is dry, no-flow duration, average groundwater flow to streams and time to recovery following the drought. Results and implications are presented in a paper submitted to Geophysical Research Letters titled, "The role of bedrock circulation depth and porosity in mountain streamflow response to prolonged drought" by Rosemary WH. Carroll, Andrew H. Manning and Kenneth H Williams. A Readme.txt file provides instructions on how to download all model files and execute each model scenario. In addition to the GSFLOW output/prms/copper_drought.csv file containing daily basin water stores and fluxes (refer to GSFLOW manual) and the output/prms/copper_drought_statvar.dat file with output defined in the gsflow3.control file (refer to GSFLOW Manual), output files also include spatially distributed daily values of total evapotranspiration, canopy evaporation, precipitation, snowfall, infiltration, snow water equivalent, potential evapotranspiration, recharge, sublimation, soil moisture, contributing interflow, water table elevations, changes in groundwater storage, groundwater evapotranspiration, interbasin groundwater flow (limited to the alluvium below the stream outlet), and surface-groundwater exchanges within the river system.

54 ENVIRONMENTAL SCIENCES↗

Reactive Transport Modeling of Shale–Fluid Interactions after Imbibition of Fracturing Fluids

Injection of hydraulic fracturing fluid (HFF) into shale formations for unconventional oil/gas production results in chemical reactions in the shale matrix. Our recent experimental study determined the depths to which different types of reactions between the shale matrix and the HFF extended. In the present study, we built continuum-scale reactive transport models to understand the coupling of chemical reactions and the transport of aqueous species in these shale–HFF systems. Calibration of the model with our previous experimental results reveals that it takes hours to months for the shale matrix to completely neutralize the imbibed acids, depending primarily upon the carbonate content of the shale. Both the HFF pH and pore pH affect the location of barite precipitation, resulting in unique barite precipitation profiles extending millimeters into calcite-rich Eagle Ford shale but only tens of micrometers into low-carbonate Marcellus shale. In addition, dissolved oxygen and extracted bitumen are key to reproducing the experimental observation of Fe(III) (oxyhydr)oxide formation in the shale matrix as a result of pyrite dissolution in the shales. A comparison between the modeling results of porosity in the present study to experimentally measured permeabilities in our previous study suggests that chemical reactions occurring at a greater depth than the observable reaction zone might have impacted permeability. Our model serves as a benchmark for efficiently modeling water–rock interactions in similar systems where bulk rock samples react with a solution in batch reactors. Important reactive transport processes were ascertained via modeling, which allows for quantitative prediction of shale–HFF interactions in shale matrices given the shale and HFF compositions.

58 GEOSCIENCES↗

Simple and Accurate One-Body Energy and Dipole Moment Surfaces for Water and Beyond

Water is often the testing ground for new, advanced force fields. While advanced functional forms for intermolecular interactions have been integral to the development of accurate water models, less attention has been paid to a transferable model for intramolecular valence terms. In this work, we present a one-body energy and dipole moment surface model, named 1B-UCB, that is simple yet accurate and can be feasibly adapted for both standard and advanced potentials. 1B-UCB for water is comparable in accuracy to those with much more complex functional forms, despite having drastically fewer parameters. The parametrization protocol has been implemented as part of the Q-Force automated workflow and requires only a quantum mechanical Hessian calculation as reference data, hence allowing it to be easily extended to a variety of molecular systems beyond water, which we demonstrate on a selection of small molecules with different symmetries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data-driven modeling of municipal water system responses to hydroclimate extremes

Sustainable western US municipal water system (MWS) management depends on quantifying the impacts of supply and demand dynamics on system infrastructure reliability and vulnerability. Systems modeling can replicate the interactions but extensive parameterization, high complexity, and long development cycles present barriers to widespread adoption. To address these challenges, we develop the Machine Learning Water Systems Model (ML-WSM) – a novel application of data-driven modeling for MWS management. We apply the ML-WSM framework to the Salt Lake City, Utah water system, where we benchmark prediction performance on the seasonal response of reservoir levels, groundwater withdrawal, and imported water requests to climate anomalies at a daily resolution against an existing systems model. The ML-WSM accurately predicts the seasonal dynamics of all components; especially during supply-limiting conditions (KGE > 0.88, PBias < ±3%). Extreme wet conditions challenged model skill but the ML-WSM communicated the appropriate seasonal trends and relationships to component thresholds (e.g., reservoir dead pool). The model correctly classified nearly all instances of vulnerability (83%) and peak severity (100%), encouraging its use as a guidance tool that complements systems models for evaluating the influences of climate on MWS performance.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

High resolution identification and quantification of diffuse deep groundwater discharge in mountain rivers using continuous boat-mounted helium measurements

Discharge of deeply sourced groundwater to streams is difficult to locate and quantify, particularly where both discrete and diffuse discharge points exist, but diffuse discharge is one of the primary controls on solute budgets in mountainous watersheds. The noble gas helium is a unique identifier of deep groundwater discharge because groundwater with long residence times is commonly enriched in helium. In this study, a portable mass spectrometer was used to measure longitudinal variation in dissolved helium concentrations in two mountainous rivers at high spatial resolution not feasible with traditional sampling techniques. Helium profiles were then simulated using a mass-balance model to quantify longitudinal variation in groundwater discharge to the receiving rivers. Results indicate helium concentrations were enriched by multiple orders of magnitude above atmospheric equilibrium in both rivers and that this persisted for up to 18 km below observed pulse inputs in the Colorado River. Helium mass-balance models match observed longitudinal patterns with the exception of sharp initial increases in helium observed in the rivers. Increased longitudinal groundwater discharge rates correspond to mapped geologic structures in both watersheds that likely transport deep geothermal water. Models show variable sensitivity to spatial assignment of input variables representing the groundwater source, illustrating the importance of collecting data from discrete groundwater discharges where possible. The methodology shows promise for field experiments designed to assess air–water exchange rates and to quantify total groundwater discharge from a combination of discrete and diffuse sources.

Deep groundwater↗

Molecular-dynamics simulation methods for macromolecular crystallography

It is investigated whether molecular-dynamics (MD) simulations can be used to enhance macromolecular crystallography (MX) studies. Historically, protein crystal structures have been described using a single set of atomic coordinates. Because conformational variation is important for protein function, researchers now often build models that contain multiple structures. Methods for building such models can fail, however, in regions where the crystallographic density is difficult to interpret, for example at the protein–solvent interface. To address this limitation, a set of MD–MX methods that combine MD simulations of protein crystals with conventional modeling and refinement tools have been developed. In an application to a cyclic adenosine monophosphate-dependent protein kinase at room temperature, the procedure improved the interpretation of ambiguous density, yielding an alternative water model and a revised protein model including multiple conformations. The revised model provides mechanistic insights into the catalytic and regulatory interactions of the enzyme. The same methods may be used in other MX studies to seek mechanistic insights.

59 BASIC BIOLOGICAL SCIENCES↗

NaCl aggregation in water at elevated temperatures and pressures: Comparison of classical force fields

The properties of water vary dramatically with temperature and density. This can be exploited to control its effectiveness as a solvent. Thus, supercritical water is of keen interest as solvent in many extraction processes. The low solubility of salts in lower density supercritical water has even been suggested as a means of desalination. The high temperatures and pressures required to reach supercritical conditions can present experimental challenges during collection of required physical property and phase equilibria data, especially in salt-containing systems. Molecular simulations have the potential to be a valuable tool for examining the behavior of solvated ions at these high temperatures and pressures. However, the accuracy of classical force fields under these conditions is unclear. We have, therefore, undertaken a parametric study of NaCl in water, comparing several salt and water models at 200 bar–600 bar and 450 K–750 K for a range of salt concentrations. We report a comparison of structural properties including ion aggregation, hydrogen bonding, density, and static dielectric constants. All of the force fields qualitatively reproduce the trends in the liquid phase density. An increase in ion aggregation with decreasing density holds true for all of the force fields. The propensity to aggregate is primarily determined by the salt force field rather than the water force field. This coincides with a decrease in the water static dielectric constant and reduced charge screening. While a decrease in the static dielectric constant with increasing NaCl concentration is consistent across all model combinations, the salt force fields that exhibit more ionic aggregation yield a slightly smaller dielectric decrement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Green synthesis of sulfur‐doped g‐C 3 N 4 nanosheets for enhanced removal of oxytetracycline under visible‐light irradiation and reduction of its N ‐nitrosodimethylamine formation potential

Abstract BACKGROUND In this study, sulfur‐doped g‐C 3 N 4 (SCN) nanosheets were synthesized using thiourea as a precursor, and then used to catalyze the degradation of oxytetracycline (OTC) under visible‐light irradiation. OTC was chosen as target contaminant because of it being an important precursor of N ‐nitrosodimethylamine (NDMA). RESULTS The removal of OTC was influenced by its initial concentration, initial pH, SCN dosage and water matrices. OTC (≤10 mg L −1 ) was almost completely removed in 40 min under the conditions of an initial pH of 7.0 and a SCN dose of 1.0 g L −1 , and its degradation was well described by the pseudo‐first‐order kinetics model. Water matrices would also influence the degradation of OTC in the system. Electron paramagnetic resonance analysis and trapping experiments confirmed that the function of the radicals for OTC removal followed the order of • O 2 − > • OH > h + . Eight transformation products were determined during the degradation of OTC, it being removed through four pathways: methyl oxidization, demethylation, decarbonylation and secondary alcohol oxidation. SCN was stable in the system, as the removal efficiency of OTC was not significantly reduced even after three recycles. In addition, 55.5% of NDMA formation potential of OTC was reduced after SCN catalytic oxidation. CONCLUSIONS The results imply that the visible‐light‐driven SCN catalytic oxidation is an effective technology not only for the removal of OTC but also for the reduction of NDMA formation potential. © 2021 Society of Chemical Industry

Dou, Yicheng↗

Height Above Nearest Drainage (HAND) and Hydraulic Property Table for CONUS

The continental flood inundation mapping (CFIM) framework is a high-performance computing (HPC)-based computational framework for the Height Above Nearest Drainage (HAND)-based inundation mapping methodology. Using the 10m Digital Elevation Model (DEM) data produced by U.S. Geological Survey (USGS) 3DEP (the 3-D Elevation Program) and the NHDPlus hydrography dataset produced by USGS and the U.S. Environmental Protection Agency (EPA), a hydrological terrain raster called HAND is computed for HUC6 units in the conterminous U.S. (CONUS). The value of each raster cell in HAND is an approximation of the relative elevation between the cell and its nearest water stream. Derived from HAND, a hydraulic property table is established to calculate river geometry properties for each of the 2.7 million river reaches covered by NHDPlus (5.5 million kilometers in total length). This table is a lookup table for water depth given an input stream flow value. Such lookup is available between water depth 0m and 25m at 1-foot interval. The flood inundation map is then computed by using HAND and this lookup table based on the near real-time water forecast from the National Water Model (NWM) at the National Oceanic and Atmospheric Administration (NOAA). HAND and the Hydraulic Property Table version 0.2. is created to correspond to data updates in the USGS 1/3 arcsec DEM, the USGS National Hydrography Dataset, including its Water Boundary Dataset, and the NHDPlus medium resolution dataset. This dataset comprises 331 HUC6 units for CONUS (excluding the five great lakes units), each is a downloadable zip file. Version 0.1 was computed at the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urban-Champaign in 2016 and is currently hosted at the Texas Advanced Computing Center (TACC). Please cite this data DOI and the following publications and data DOIs when you use HAND and the hydraulic property table: Liu, Yan Y., David R. Maidment, David G. Tarboton, Xing Zheng, and Shaowen Wang. 'A CyberGIS integration and computation framework for high-resolution continental-scale flood inundation mapping.' JAWRA Journal of the American Water Resources Association 54, no. 4 (2018): 770-784. DOI: 10.1111/1752-1688.12660 Zheng, Xing, David G. Tarboton, David R. Maidment, Yan Y. Liu, and Paola Passalacqua. 'River channel geometry and rating curve estimation using height above the nearest drainage.' JAWRA Journal of the American Water Resources Association 54, no. 4 (2018): 785-806. DOI: 10.1111/1752-1688.12661 Liu, Y. (2018). Height Above Nearest Drainage (HAND) for CONUS - v0.1, HydroShare, https://doi.org/10.4211/hs.69f7d237675c4c73938481904358c789 LICENSE FOR USE -- MAPS AND DATA DISCLAIMER This resource is shared under the Creative Commons Attribution CC BY, http://creativecommons.org/licenses/by/4.0/ MAPS AND DATA DISCLAIMER The Oak Ridge National Laboratory (ORNL) shall not be held liable for improper or incorrect use of the data described or information contained on this map or associated series of maps. The data and related map graphics are not legal, land survey or engineering documents and are not intended to be used as such. ORNL gives no warranty, express or implied, as to the accuracy, reliability, utility or completeness of this information. The user of these maps and data assumes all responsibility and risk for the use of the maps and data. ORNL disclaims all warranties, representations or endorsements either express or implied, with regard to the information contained in this map product, including, but not limited to, all implied warranties of merchantability, fitness for a particular purpose or non-infringement. This preliminary map product is for research and review purposes only. It is not intended to be used for emergency management operational or life safety decisions at the local or regional governmental level or by the general public. Users requiring information regarding hazardous conditions or meteorological conditions for specific geographic areas should consult directly with their city or county emergency management office.

54 ENVIRONMENTAL SCIENCES↗

TOUGH3/EOS7MG (EOS7MG) v1.1

EOS7MG is a new TOUGH3 module for modeling water, brine, and multiple gas mixtures in the subsurface multiphase flow system. The module allows mixture of as more as three gas components selecting from a list of predefined gases (CH4, C2H6, C3H8, H2S, CO2, N2, NO2, H2, and AIR). EOS7MG was developed based on EOS7C and inherited the general modeling capabilities of the TOUGH3 platform. It uses cubic equation of states for gas density, viscosity, and enthalpy calculation. The module provides the selection options for Peng-Robinson, Redlich-Kwong, or Soave-Redlich-Kwong equations of state. The subsurface flow and transport of gas and aqueous phase mixtures over a wide range of pressures and temperatures is modeled with a multiphase Darcy's Law and an accurate chemical equilibrium approach as originally implemented in EOS7C is used for calculation of the solubilities of different mass components. EOS7MG was designed to allow flexible number of components based on the number of gases included in the model. The potential application of this module may include subsurface gas storage, energy storage, CCS, enhanced gas recovery, and more.

Zhang, Keni↗

Tethys: A Spatiotemporal Downscaling Model for Global Water Demand

Humans use water for many important tasks, such as drinking, growing food, and cooling power plants. Since future water demands depend on complex global interactions between economic sectors (e.g., demand for wheat in one country causing demand for water to grow that wheat in another country), it is often modeled at coarse spatial and temporal scales as part of models that account for complex, multi-sector system dynamics. However, models that project future water availability typically simulate physical processes at much finer scales. Tethys enables integration between these kinds of models by downscaling region-scale water demand projections using sector-specific proxies and formulas.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

FY-25 Progress on Computational Modeling of the Water Based NSTF

This report summarizes the system level modeling using RELAP5-3D of the Natural Convection Shutdown Heat Removal Test Facility (NSTF) completed in FY25. This year’s work focuses on a new tank configuration where the inlet of the tank was lowered in elevation by 45”. The stability boundaries of the NSTF are thoroughly studied and stability maps are constructed based on the stability and the oscillation patterns of the system. Five distinct operational modes are identified, namely single-phase liquid, uniform double peak oscillations, uniform sinusoidal oscillations, stable two-phase flow, and non-uniform oscillations. Next, the riser inlet throttling case of experimental test Run-104 is simulated with the RELAP5 model where good agreement is obtained between the model and the experimental data. The simulation also highlights the effects of backflow of water from the tank to the upper region of the chimney. Additionally, the decay heat removal test of Run-99 is simulated with the RELAP5 model. Comparison is carried out between this run and a similar run with the mid-tank inlet of Run-74 performed in FY22. With the lower tank inlet, the RELAP5 model is able to predict the experimental data more accurately than the previous mid tank inlet configuration. The discrepancy in model prediction accuracy highlights the non-symmetrical spatial effects in the tank that would otherwise be more easily captured with higher fidelity models. Lastly, two exploratory studies are conducted to investigate the behaviors of the NSTF when 1) heating is provided to the downcomer and 2) a bypass channel is added between the horizontal chimney section to the downcomer.

42 ENGINEERING↗

Development of an Amine Oxide Polyzwitterion Brush Martini Model with Polarizable Water and Ions

Abstract In order to accurately simulate the fouling process of proteins onto polyzwitterion brushes, models that accurately capture the hydration properties and chain conformations of such brushes must first be established. We developed a Martini coarse-grained (CG) model for amine oxide polyzwitterion (PNOMA) brushes, a promising class of antifouling materials, in polarizable water and ions by fitting to all-atom bond and angle distributions, monomer hydration free energy, monomer–monomer distance potential of mean force (PMF), and monomer–salt radial distribution functions (RDFs). Martini 2.2P was selected for compatibility with the established polarizable water and ion models. For comparison with PNOMA, we also constructed models for conventional sulfobetaine (PSBMA) and phosphorylcholine (PMPC) polyzwitterions and the polycation PMETAC using established nonbonded bead types from the literature and refitting bond and angle potentials. We simulated each polymer brush chemistry for varying grafting density and chain length, validating brush height scaling relations against experimental data. The CG models captured the relative hydration strengths among different polyzwitterion chemistries, and brush heights extrapolated to higher molecular weights are in agreement with experimental ellipsometry data. We find that chain swelling of the superhydrophilic PNOMA brushes lies between that of the traditional polyzwitterions PSBMA/PMPC and the polycation PMETAC. For PNOMA brushes in NaCl solution, simulated brush height decreases with salt concentration due to the selectively strong interactions between amine oxide and sodium ions.

Walker, Christopher C. [Oak Ridge National Laborat↗

Understanding Differences in Water Adsorption Isotherms: Structural Variations, Force Fields, and Monte Carlo Simulation Approaches

Accurate prediction of water adsorption in micro- and mesoporous materials with hydrophobic pores is essential for the design and characterization of advanced adsorbent materials for separation and energy applications. Here, we assess the reproducibility and consistency of water adsorption isotherms in two microporous all-silica MFI zeolite structures (MFI-K and MFI-O) using two different zeolite force fields and three simulation approaches: grand canonical Monte Carlo (GCMC), Gibbs ensemble Monte Carlo (GEMC), and transition matrix Monte Carlo (TMMC). We demonstrate that consistent treatment of the bulk fluid phase in GCMC and TMMC simulations is critical for reconciling isotherms across methods, and we construct simulation-based equations of state for the TIP4P water model to enable rigorous fugacity-to-pressure conversions. Large shifts in the isotherms are observed for two zeolite force fields developed using different parametrization strategies, with the GCS force field representing implicitly a defect-containing all-silica zeolite, whereas the TraPPE-zeo force field accurately represents an essentially defect-free all-silica zeolite. While water in the van Koningsveld structure of MFI exhibits a first-order phase transition and condensation-like step for adsorption near room temperature, water in the Olson structure of MFI displays continuous adsorption, attributed to differences in the adsorption free energy landscapes. Structural analysis reveals that small geometric variations, particularly Si–O–Si bond angles near the strongest adsorption sites, lead to these substantial differences in adsorption behavior. Furthermore, our results highlight the sensitivity of simulated water adsorption isotherms in hydrophobic frameworks to seemingly small differences in the framework structures, force field parametrization, and simulation approaches.

36 MATERIALS SCIENCE↗

Height Above Nearest Drainage (HAND) and Hydraulic Property Table for CONUS - Version 0.21 (20200601)

The continental flood inundation mapping (CFIM) framework is a high-performance computing (HPC)-based computational framework for the Height Above Nearest Drainage (HAND)-based inundation mapping methodology. Using the 10m Digital Elevation Model (DEM) data produced by U.S. Geological Survey (USGS) 3DEP (the 3-D Elevation Program) and the NHDPlus hydrography dataset produced by USGS and the U.S. Environmental Protection Agency (EPA), a hydrological terrain raster called HAND is computed for HUC6 units in the conterminous U.S. (CONUS). The value of each raster cell in HAND is an approximation of the relative elevation between the cell and its nearest water stream. Derived from HAND, a hydraulic property table is established to calculate river geometry properties for each of the 2.7 million river reaches covered by NHDPlus (5.5 million kilometers in total length). This table is a lookup table for water depth given an input stream flow value. Such lookup is available between water depth 0m and 25m at 1-foot interval. The flood inundation map is then computed by using HAND and this lookup table based on the near real-time water forecast from the National Water Model (NWM) at the National Oceanic and Atmospheric Administration (NOAA). HAND and the Hydraulic Property Table version v0.21 is an upgrade to v0.2. Version 0.21 applies NHD HR etching to DEMs for all HUC6 units before running the HAND workflow. This new version also fixed the issue of void areas along HUC boundary. This dataset comprises 331 HUC6 units for CONUS (excluding the five great lakes units), each is a downloadable zip file. Version 0.1 was computed at the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urban-Champaign in 2016 and is currently hosted at the Texas Advanced Computing Center (TACC). Please cite this data DOI and the following publications and data DOIs when you use HAND and the hydraulic property table: Liu, Yan Y. Height Above Nearest Drainage (HAND) and Hydraulic Property Table for CONUS - Version 0.2. (20200301). Oak Ridge Leadership Computing Facility. (2020). DOI: 10.13139/ORNLNCCS/1608331 Liu, Yan Y., David R. Maidment, David G. Tarboton, Xing Zheng, and Shaowen Wang. 'A CyberGIS integration and computation framework for high-resolution continental-scale flood inundation mapping.' JAWRA Journal of the American Water Resources Association 54, no. 4 (2018): 770-784. DOI: 10.1111/1752-1688.12660 Zheng, Xing, David G. Tarboton, David R. Maidment, Yan Y. Liu, and Paola Passalacqua. 'River channel geometry and rating curve estimation using height above the nearest drainage.' JAWRA Journal of the American Water Resources Association 54, no. 4 (2018): 785-806. DOI: 10.1111/1752-1688.12661 Liu, Y. (2018). Height Above Nearest Drainage (HAND) for CONUS, HydroShare, https://doi.org/10.4211/hs.69f7d237675c4c73938481904358c789 LICENSE FOR USE -- MAPS AND DATA DISCLAIMER This resource is shared under the Creative Commons Attribution CC BY, http://creativecommons.org/licenses/by/4.0/ MAPS AND DATA DISCLAIMER The Oak Ridge National Laboratory (ORNL) shall not be held liable for improper or incorrect use of the data described or information contained on this map or associated series of maps. The data and related map graphics are not legal, land survey or engineering documents and are not intended to be used as such. ORNL gives no warranty, express or implied, as to the accuracy, reliability, utility or completeness of this information. The user of these maps and data assumes all responsibility and risk for the use of the maps and data. ORNL disclaims all warranties, representations or endorsements either express or implied, with regard to the information contained in this map product, including, but not limited to, all implied warranties of merchantability, fitness for a particular purpose or non-infringement. This preliminary map product is for research and review purposes only. It is not intended to be used for emergency management operational or life safety decisions at the local or regional governmental level or by the general public. Users requiring information regarding hazardous conditions or meteorological conditions for specific geographic areas should consult directly with their city or county emergency management office.

54 ENVIRONMENTAL SCIENCES↗