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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Stand-Alone and Hybrid Electric Thermal Energy Storage in the System Advisor Model

This project developed stand-alone electric-thermal energy storage (ETES), stand-alone pumped thermal energy storage (PTES), and hybrid molten-salt power tower (MSPT)-ETES performance and dispatch optimization techno-economic models. The models are available to the public through the System Advisor Model (SAM) software, scripting, and as open-source code. We compared results of the dispatch model to PLEXOS dispatch of a similar generator using the same initial grid pricing signal and found our dispatch model performed well, but closer agreement between the models was limited by the inherent differences between price-taker and unit commitment models. Nevertheless, the price-taker models developed in this project are useful to analyze proposed ETES and PTES technologies because they provide more detailed system and component models, solve several orders of magnitude faster, and are available as free open-source software. The model results represent the most optimistic returns considering grid arbitrage from the input electricity pricing, so the financial results can be applied as a feasibility stage-gate. We also submitted a journal draft paper that describes the ETES dispatch model methodology and demonstrates model functionality. An accepted journal article will serve as peer-reviewed documentation for the models, along with the open-source code, SAM help-menu content, and eventually this final project report.

14 SOLAR ENERGY↗
DOE OSTI2021

Review of WEC-Sim Development and Applications

WEC-Sim (Wave Energy Converter Simulator) is an open-source code for simulating wave energy converters that has been actively developed and applied to simulate a wide variety of device archetypes, and has become a popular tool since its release. This paper reviews the development efforts and usage of WEC-Sim. The publications considered in this study have been broken down into six topic areas, namely, feature development, experimental validation, device modelling, control modelling, powertake-off (PTO) and grid modelling, and novel applications, which includes some non-wave energy applications. This review paper also recognizes the contributions of academic researchers and technology developers from around the world toward the broader WEC-Sim development effort. The growing number of external applications of WEC-Sim demonstrates a broader acceptance of the open-source code, and the ways WEC-Sim has been used in certain topic areas also highlight potential future development needs.

applications↗
DOE OSTI2022

Review of WEC-Sim development and applications

WEC-Sim (Wave Energy Converter Simulator) is an open-source code for simulating wave energy converters, which has been actively developed and applied to simulate a wide variety of device archetypes, and has become a popular tool since its release. This paper reviewed the development efforts and the usage of WEC-Sim. The publications considered in this study have been broken down into six topic areas, namely feature development, experimental validation, device modeling, control modeling, PTO and grid modeling, and novel applications, which even includes some non-wave energy applications. This review paper has also attempted to recognize the contributions of the broader WEC-Sim development effort, meaning not only the internal WEC-Sim development team but also the external efforts from the academia researchers and technology developers around the world. The growing trend of external applications of WEC-Sim has demonstrated the broader acceptance of the open-source code, and how WEC-Sim has been used in a certain topic area also highlights the potential future development needs.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

GNET2: an R package for constructing gene regulatory networks from transcriptomic data

Abstract Motivation The Gene Network Estimation Tool (GNET) is designed to build gene regulatory networks (GRNs) from transcriptomic gene expression data with a probabilistic graphical model. The data preprocessing, model construction and visualization modules of the original GNET software were developed on different programming platforms, which were inconvenient for users to deploy and use. Results Here, we present GNET2, an improved implementation of GNET as an integrated R package. GNET2 provides more flexibility for parameter initialization and regulatory module construction based on the core iterative modeling process of the original algorithm. The data exchange interface of GNET2 is handled within an R session automatically. Given the growing demand for regulatory network reconstruction from transcriptomic data, GNET2 offers a convenient option for GRN inference on large datasets. Availability and implementation The source code of GNET2 is available at https://github.com/jianlin-cheng/GNET2. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Monte Carlo calculation and verification of the geometrical factors for the NPDGamma experiment

The NPDGamma experiment measures the parity-violating asymmetry in gamma-ray emission in the capture of polarized neutrons on liquid parahydrogen. The sensitivity to the asymmetry for each detector in the array is used as a parameter in the extraction of the physics asymmetry from the measured data. The detector array is approximately cylindrically symmetric around the target and a step-wise sinusoidal function has been used for the sensitivity in the previous iteration of the NPDGamma experiment, but deviations from cylindrical symmetry necessitate the use of a Monte Carlo model to determine corrections to the geometrical factors. For the calculations, source code modifications to MCNPX were done in order to calculate the sensitivity of each cesium iodide detector to the physics asymmetry. We describe the MCNPX model and results from calculations and how the results are validated through measurement of the parity violating asymmetry of gamma-rays from neutron capture on chlorine.

Grammer, K. B.↗
DOE OSTI2021

Model, data, and code for paper "Modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x"

The data package includes data, model, and code that support the analyses and conclusions in the paper titled “modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x”. The primary goal of this paper is to demonstrate that key streamflow properties such as water depth, flow velocity, and dynamic pressure in a natural river at 30-kilometer scale over 5 years can be reliably and efficiently modeled using the computational framework presented in this paper. To support the paper, various data types from remote sensing, field observations, and computational models are used. Specific details are described as follows. Firstly, the river bathymetry data was obtained from a Light Detection and Ranging (LiDAR) survey. This data is then converted to a triangulated surface format, STL, for mesh generation in OpenFOAM. The STL data can be found in Model_Setups/BaseCase_2013To2015/constant/triSurface. The OpenFOAM mesh generated using this STL file can be found in constant/polyMesh. Other model setups, boundary and initial conditions can be found in /system and /0.org under folder BaseCase_2013To2015. A similar data structure can also be found in BaseCase_2018To2019 for the simulations during 2018 and 2019. Secondly, the OpenFOAM simulations need the upstream discharge and water depth information at the upstream boundary to drive the model. These data are generated from a one-dimensional hydraulic model and the data can be found under the folder Model_Setups /1D model Mass1 data. The mass1_65.csv and mass1_191.csv files include the results of the 1D model at the model inlet and outlet, respectively. The Matlab source code Mass1ToOFBC20182019.m is used to convert these data into OpenFOAM boundary condition setups.With the above OpenFOAM model, it can generate data for water surface elevation, flow velocity, and dynamic pressure. In this paper, the water surface elevation was measured at 7 locations during different periods between 2011 and 2019. The exact survey locations (see Fig1_SurveyLocations.txt) can be found in folder Fig_1. The variation of water stage over time at the 7 locations can be found in folder /Observation_WSE. The data type include .txt, .csv, .xlsx, and .mat. The .mat data can be loaded by Matlab.We also measured the flow velocities at 12 cross-sections along the river. At each cross-section, we recorded the x, y locations, depth, three velocity components u,v,w. These data are saved to a Matlab format which can be found under folder /Observation_Velocity and /Fig_1. The relative locations of velocity survey locations to the river bathymetry can be found in Figure 1c.The water stage data at the 7 locations from OpenFOAM, 1D, and 2D hydraulic models are also provided to evaluate the long-term performance of 3D models vs 1D/2D models. The water stage data for the 7 locations from OpenFOAM have been saved to .mat format and can be found in /OpenFOAM_WSE. The water stage data from the 1D model are saved in .csv format and can be found in /Mass1_WSE. The water stage from the 2D model is saved as .mat format and can be found in / Mass2_WSEIn addition, the OpenFOAM model outputs the information of hydrostatic and hydrodynamic pressure. They are saved as .mat format under folder /Fig_11/2013_1. As the files are too large, we only uploaded the data for January 2013. The area of different ratio of dynamic pressure to static pressure for all simulation range, i.e., 2013-2015, are saved to .mat format. They can be found in /Fig_11/PA. Further, the data of wall clock time versus the solution time of the OpenFOAM modeling are also saved to .mat format under folder /Fig_13/LogsMat. In summary, the data package contains seven data types, including .txt, .csv, .xlsx, .dat, .stl, .m, and .mat. The former 4 types can be directly open using a text editor or Microsoft Office. The .mat format needs to be read by Matlab. The Matlab source code .m files need to be run with Matlab. The OpenFOAM setups can be visualized in ParaView. The .stl file can be opened in ParaView or Blender. The data in subfolders Fig_1 to Fig_10 and Fig_12 are copied from the aforementioned data folders to generate specific figures for the paper. A readME.txt file is included in each subfolder to further describe how the data in each folder are generated and used to support the paper.Please use the data package's DOI to cite the data package. Please contact yunxiang.chen@pnnl.gov if you need more data related to the paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Symmetry-mode analysis for local structure investigations using pair distribution function data

Symmetry-adapted distortion modes provide a natural way of describing distorted structures derived from higher-symmetry parent phases. Structural refinements using symmetry-mode amplitudes as fit variables have been used for at least ten years in Rietveld refinements of the average crystal structure from diffraction data; more recently, this approach has also been used for investigations of the local structure using real-space pair distribution function (PDF) data. Here, the value of performing symmetry-mode fits to PDF data is further demonstrated through the successful application of this method to two topical materials: TiSe2, where a subtle but long-range structural distortion driven by the formation of a charge-density wave is detected, and MnTe, where a large but highly localized structural distortion is characterized in terms of symmetry-lowering displacements of the Te atoms. Here, the analysis is performed using fully open-source code within the DiffPy framework via two packages developed for this work: isopydistort, which provides a scriptable interface to the ISODISTORT web application for group theoretical calculations, and isopytools, which converts the ISODISTORT output into a DiffPy-compatible format for subsequent fitting and analysis. These developments expand the potential impact of symmetry-adapted PDF analysis by enabling high-throughput analysis and removing the need for any commercial software.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Simulating a Mesoscale Convective System Using WRF with a New Spectral Bin Microphysics: Part 1: Hail vs Graupel

A modified Fast Spectral Bin Microphysics scheme (FSBM-2) embedded into the Weather Research and Forecasting Model (WRF) is used to simulate a mesoscale deep convective system observed during the Midlatitude Continental Convective Clouds Experiment (MC3E). FSBM-2 uses modified source codes as compared to the current FSBM (FSBM-1). In contrast to FSBM-1, FSBM-2 can simulate hail of several cm in diameter and includes additional processes such as spontaneous breakup of raindrops and aerosol regeneration by drop evaporation. It is shown that allowing large hail particles of diameters exceeding about 1 cm substantially increases the agreement between the simulated and observed squall-line structures both in the convective and stratiform regions. In contrast, if graupel particles are used to represent high-density hydrometeors in convective areas, the ratio of convective-to-stratiform areas diverges from the ratio seen in observations and maximum radar reflectivities are substantially underestimated. Analysis of snow size distributions in the stratiform area shows an important link between the ice crystals formed by homogeneous freezing in the convective area to ice particle number concentration in the stratiform region. Simulated raindrop size distributions in the stratiform area below the melting level from FSBM-2 show a good agreement with observations. The regeneration of CCN by droplet evaporation and detrainment of these CCN to the stratiform region increases the concentration of CCN there up to 8-9 km altitude; the additional CCN penetrate clouds and produce new droplets, leading to some convection intensification. Key words: Mesoscale convective systems (MCS), squall lines, spectral bin microphysics, large hail, in-cloud nucleation, size distributions of hydrometeors in MCS.

Shpund, Kobby↗
DOE OSTI2017

Automatic and Transparent Resource Contention Mitigation for Improving Large-Scale Parallel File System Performance

Proportional to the scale increases in HPC systems, many scientific applications are becoming increasingly data intensive, and parallel I/O has become one of the dominant factors impacting the large-scale HPC application performance. On a typical large-scale HPC system, we have observed that the lack of a global workload coordination coupled with the shared nature of storage systems cause load imbalance and resource contention over the end-to-end I/O paths resulting in severe performance degradation. I/O load imbalance on HPC systems is generally a self-inflicted wound and mostly occurs between the I/O paths and resources consumed by each individual job. In this paper, we introduce TAPP-IO, a dynamic, shared load balancing framework for mitigating resource contention. TAPP-IO extends our previous work and solves two major limitations: First, it transparently intercepts file creation calls during runtime to balance the workload over all available storage targets. The usage of TAPP-IO requires no application source code modifications and is independent from any I/O middleware. The framework can be applied to almost any HPC platform and is suitable for systems that lack a centralized file system resource manager. Second, the framework proposes a new placement strategy to support not only file-per-process I/O, but also single shared file I/O. This opens the door to a new class of scientific applications that can leverage the placement library for improved performance. We demonstrate the effectiveness of our integration on the Titan system at the Oak Ridge National Laboratory. Our experiments with a synthetic benchmark and real-world HPC workload show that, even in a noisy production environment, TAPP-IO can improve large-scale application performance significantly.

Neuwirth, Sarah↗
DOE OSTI2024

Globally Gridded Groundwater Extraction Volumes and Costs under Six Depletion and Ponded Depth Targets

This repository contains simulated outputs from superwell – a hydro-economic tool for long-term assessment of groundwater cost and supply – providing globally gridded groundwater extractable volumes and associated unit costs ($/km³) for accessible groundwater production, based on a variety of user-defined depletion and ponded depth scenarios. Key model documentation: Niazi, H., Ferencz, S. B., Graham, N. T., Yoon, J., Wild, T. B., Hejazi, M., Watson, D. J., & Vernon, C. R. (2025). Long-term hydro-economic analysis tool for evaluating global groundwater cost and supply: Superwell v1.1. Geoscientific Model Development, 18(5), 1737-1767. https://doi.org/10.5194/gmd-18-1737-2025 Find the source code of the superwell model on GitHub: https://github.com/JGCRI/superwell Repository Overview Main output: superwell_outputs.7z contains 6 files (4.5 GB) named as superwell_py_deep_all_0.*PD_0.*DL.csv. These files present superwell outputs of global groundwater extraction volumes and cost estimates on a 0.5° scale for six scenarios with different Ponded Depth (PD; 0.3 and 0.6 m) and Depletion Limit (DL; 5%, 25%, and 40% of available volume) targets over the entire pumping lifetime of a grid cell superwell_py_deep_all_0.3PD_0.25DL_sample_100.csv contains superwell outputs for 100 data points sampled to match the global inputs' distribution superwell_py_deep_all_0.3PD_0.25DL_Grid_72548.csv contains superwell output for a single grid cell concept_v5.png provides an overview of the superwell workflow Outputs Description year_number: year of pumping depletion_limit: set depletion limit (DL) as a volume fraction of total available groundwater Mappings: continent, country, gcam_basin_id, Basin_long_name, grid_id: geographic identifiers and basin information Inputs: grid_area (km²): area of the grid cell whyclass: hydrogeological classification of the aquifer permeability (m/day), porosity (%), total_thickness (m), depth_to_water (m): aquifer properties. The geo-processed input data has been published separately: https://doi.org/10.57931/2307831 Model outputs: orig_aqfr_sat_thickness (m), aqfr_sat_thickness (m): original and remaining/instantaneous saturated thickness of the aquifer hydraulic_conductivity (m/day), transmissivity (m²/day): hydraulic properties of the aquifer radius_of_influence (m), areal_extent (km²): well radius and area of influence from the center of the well number_of_wells (-): number of wells in a grid cell determined by a ratio of well area and grid area max_drawdown (m), drawdown (m), drawdown_interference (m): well and aquifer drawdown during extraction total_head (m): total lift for the groundwater (depth to water plus drawdown) total_well_length (m): total depth of wells drilled well_yield (m³/day): pumping rate or well yield power (kW), energy (kWh): power and energy required for pumping groundwater Volume Outputs: volume_produced_perwell (m³), cumulative_vol_produced_perwell (m³): production volume metrics per well volume_produced_allwells (m³), cumulative_vol_produced_allwells (m³): aggregate extraction volumes for all wells in a grid cell available_volume (m³): available groundwater in storage for the grid cell as determined by aquifer properties depleted_vol_fraction: fraction of total volume pumped over available volumes in a grid cell (same as depletion limit) Cost Outputs: well_installation_cost ($): well installation cost based on the hydrogeological complexity of the aquifer annual_capital_cost, maintenance_cost, nonenergy_cost ($): nonenergy costs energy_cost_rate ($/kWh): electricity rate energy_cost ($): energy cost of pumping groundwater total_cost_perwell ($), total_cost_allwells ($): total annual energy and non-energy cost for each and all wells in a grid cell a unit_cost ($/m³), unit_cost_per_km3 ($/km³), unit_cost_per_acreft ($/acre-ft): total cost of pumping a unit of groundwater, indicated for different spatial units Key Resources Model documentation: Niazi, H., Ferencz, S., Graham, N., Yoon, J., Wild, T., Hejazi, M., Watson, D., & Vernon, C. (2024; In-prep). Long-term Hydro-economic Assessment Tool for Evaluating Global Groundwater Cost and Supply: Superwell v1. Geoscientific Model Development. Input data: Niazi, H., Watson, D., Hejazi, M., Yonkofski, C., Ferencz, S., Vernon, C., Graham, N., Wild, T., & Yoon, J. (2024). Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins. MSD-LIVE Data repository. https://doi.org/10.57931/2307831 superwell source code: https://github.com/JGCRI/superwell Cite as Niazi, H., Ferencz, S., Yoon, J., Graham, N., Wild, T., Hejazi, M., Watson, D., & Vernon, C. (2024). Globally Gridded Groundwater Extraction Volumes and Costs under Six Depletion and Ponded Depth Targets. MSD-LIVE Data repository. https://doi.org/10.57931/2307832 Contact Reach out to Hassan Niazi or Stephen Ferencz or open an issue in the superwell repository for questions or suggestions.

Earth Systems↗
DOE OSTI2021

UEMtomaton: A Source-Available Platform to Aid in Start-up of Ultrafast Electron Microscopy Labs

The steady rise in the number of ultrafast electron microscopy (UEM) labs, in addition to the opacity and lack of detailed descriptions of current approaches that would enable point-by-point construction, has created an opportunity for sharing common methods and instrumentation for (for example) automating data acquisition to assist in efficient lab start-up and to learn about common and robust protocols. In the spirit of open sharing of methods, we provide here a description of an entry-level method and user interface (UI) for automating UEM experiments, and we provide access to the source code and scripts (source-available) for ease of implementation or as a starting reference point for those entering or seeking to enter the field (https://github.com/CEMSFlannigan/UEMtomaton/releases/tag/v1.0). Core instrumentation and physical connections in the UEM lab at Minnesota are described. Interface communication schemes consisting of duo server-client pairs between critical components – the optical delay stage and the UEM digital camera – are presented, with emphasis placed on describing the logic and communications sequence designed to conduct automated series acquisitions. An application designed and programmed with C++/CLI as Windows Forms in Microsoft Visual Studio – dubbed UEMtomaton – is also presented. Key to the UI layout is centralization of the automation tasks and establishment of communication within the software rather than by interfacing with each individual workstation. It is our hope that this note provides useful insight for current and future UEM researchers, particularly with respect to generalizability and portability of the approach to emerging labs. Here, we note that while this basic, entry-level approach is certainly not the most sophisticated or comprehensive of those currently in use, we feel there is nevertheless value in clearly communicating a proven straightforward method to hopefully lower the barrier to entry into the field.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Software Quality Assurance, Software Requirements and Gap Analysis for the MOOSE-Based Open-Source Multiphysics Code Cardinal

Cardinal continuous development and improvement efforts have led to the software being considered as a high-fidelity design and licensing tool for key areas of nuclear reactor relevant physics, including neutron transport, fluid flow, heat transfer, and mechanical processes. The fast development and expansion of the software from a pure R&D framework towards its application in the nuclear industry and regulation require a focus on maintaining and enhancing Cardinal’s software quality through strict adherence to a Software Quality Assurance (SQA) framework. To facilitate compliance with SQA standards, the Cardinal SQA Program has been initiated during Fiscal Year 2023 (FY23).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

MCNP® Code Version 6.3.1: Build Guide (Rev. 1)

This is a build guide for the MCNP® code, version 6.3.1, that expands upon the README.md included with the source code. It covers compilers, dependencies, building, testing, and installing the code in one of its supported configurations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Model Inputs, Outputs, and Scripts associated with: “Spatial microbial respiration variations in the hyporheic zones within the Columbia River Basin”

This data package is associated with the publication “Spatial microbial respiration variations in the hyporheic zones within the Columbia River Basin” published in the Journal of Geophysical Research: Biogeosciences (Son et al. 2022) available at doi: 10.1029/2021JG006654. This data package includes the key model inputs/outputs of the river corridor model for the Columbia River Basin (CRB) and the model source codes, which were used in the manuscript. The model is a carbon-nitrogen-coupled river corridor model (RCM), and the model is used to quantify hyporheic zone (HZ) aerobic and anaerobic respiration at the NHDPLUS stream reach scales. The RCM used in this study combines empirical substrate models derived from observations and three microbially driven reactions to compute respiration of the HZ for each National Hydrography Dataset (NHD) reach within the CRB. The reactions in HZs of each NHD reach include anaerobic respiration and two-step anaerobic respiration via denitrification. Our HZ respiration estimates are limited to the lotic (or flowing) stream/river systems, and do not account for the respiration process in water column. Note that the RCM only simulates the HZ’s contribution to the dissolved carbon dioxide (CO2) concentrations in the streams, and the CO2 emissions to the atmosphere are not modelled. The model computes at hourly timesteps because of the fast reaction rates. The key input data of the model are exchange flux, residence time, and stream solute (dissolved organic carbon (DOC), dissolved oxygen (DO), and nitrate concentrations). These inputs are constant over time and represent long-term averaged values.This modeling framework successfully quantified HZ respiration components over multiple scales. It revealed key mechanisms driving the spatial variation of HZ aerobic and anaerobic respiration in reaches with varying hydrologic and substrate conditions. Thus, this modeling study offers a testing hypothesis in different river system (e.g., climate and biomes) for the HZ respiration processes, and can be used as a sampling design tool for large-scale HZ experimental studies.This dataset contains five folders: (1) model_inputs, (2) model_outputs, (3) Rscripts, (4) figures, and (5) model_codes. It also contains a readme, file level metadata (FLMD), and data dictionary (dd). Please see the FLMD for a list of all the files contained in this data package and descriptions for each. The model_inputs folder contains the model inputs used to drive the model simulations. The model_outputs folder contains key model output files from the river corridor model. The Rscripts folder contains the Rscripts for pre- and post- processing model results. The figures folder contains the raw figures associated with the manuscript. The model_codes folder includes key model source codes/input files. All files are .jpg, .jpeg, .out, .e, .od, .dat, .sub, .F90, .0, .R, .sbx, .cpg, .sbn, .shx, .shp, .dbf, .prj, .tfw, .tif, .xml, .pdf, or .csv.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Model Inputs, Outputs, and Scripts associated with: “Combined effects of stream hydrology and land use on basin-scale hyporheic zone denitrification in the Columbia River Basin”

This data package is associated with the publication “Combined effects of stream hydrology and land use on basin‐scale hyporheic zone denitrification in the Columbia River Basin”, published in Water Resource Research (Son et al.2022) available at https://doi.org/10.1029/2021WR031131. This data package includes the key model inputs/outputs of the river corridor model for the Columbia River Basin (CRB) and the model source codes used in the manuscript. The model is a carbon-nitrogen-coupled river corridor model (RCM), and the model is used to quantify hyporheic zone (HZ) denitrification at the NHDPLUS stream reach scales. The RCM used in this study combines empirical substrate models derived from observations and three microbially driven reactions, including two-step denitrification and aerobic respiration, are considered within the HZ. The key input data of the model are exchange flux, residence time, and stream solute (dissolved organic carbon (DOC), dissolved oxygen (DO), and nitrate concentrations). These inputs are constant over time and represent long-term averaged values. This study uses the RCM to explore the spatial patterns of HZ denitrification across reaches with different sizes and land use in the CRB. Our main objective is to use the RCM as a virtual reality model, and the machine-learning models as surrogates that encapsulate the complexities of the physics-based model while identifying the importance of different variables that are not evident in the model conceptualization. We do not include a direct comparison of the modeled HZ denitrification and measurements; however, the RCM can capture the overall spatial patterns of the HZ denitrification because the model inputs and its reaction networks are based on well-established theory and a physical-based model. The combination of the model-based predictions and a machine-learning approach (e.g., random forest) is used to improve our understanding of what variables of the model are associated with spatial patterns of the modeled denitrification across reaches with different sizes and land uses, and to develop a proxy model using measurable variables to reproduce the simulated patterns.This dataset contains five folders: (1) model_inputs, (2) model_outputs, (3) Rscripts, (4) figures, and (5) model_codes. It also contains a readme, file level metadata (FLMD), and data dictionary (dd). Please see the FLMD for a list of all the files contained in this data package and descriptions for each. The model_inputs folder contains the model inputs used to drive the model simulations. The model_outputs folder contains key model output files from the river corridor model. The Rscripts folder contains the Rscripts for pre- and post- processing model results. The figures folder contains the raw figures associated with the manuscript. The model_codes folder includes key model source codes/input files. All files are .jpg, .jpeg, .out, .e, .od, .dat, .sub, .F90, .0, .R, .sbx, .cpg, .sbn, .shx, .shp, .dbf, .prj, .tfw, .tif, .xml, .pdf, or .csv.

54 ENVIRONMENTAL SCIENCES↗