Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Subsurface”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Using Radiogenic Noble Gas Nuclides to Identify and Characterize Rock Fracturing

Abstract Fracture‐released radiogenic noble gas nuclides are used to identify locations and constrain the volume of new fracture creation during subsurface detonations. Real‐time, in situ noble gases and reactive gases were monitored using a field‐deployed mass spectrometer and automated sampling system in a multilevel borehole array. Released gases were measured after two different detonations having distinct energy, pressure, and gas volume characteristics. Explosive‐derived gases (N 2 O, CO 2 ) and excess radiogenic 4 He and 40 Ar above atmospheric background are used to identify locations of gas transport and new fracture creation after each detonation. Fracture‐released radiogenic 4 He is used to constrain the volume of newly created fractures with a model of helium release from fracturing. Explosive by‐product gas was observed in multiple locations both near and distal to the shot locations for both detonations. Radiogenic 4 He and 40 Ar release from rock damage was observed in locations near the detonation after the second, more powerful detonation. Observed 4 He response is consistent with a model of diffusive release from newly created fractures. Volume of new fractures estimated from the 4 He release ranges from 1 to 5 m 2 with apertures ranging from 0.1 to 1 m. Our results provide evidence that radiogenic noble gases released during fracture creation can be identified at the field scale in real time and used to identify timing and location of fracture creation during deformation events. This technique could be useful in subsurface science and engineering problems where the location and amount of newly created rock fracturing is of interest including fault rupture, mine safety, subsurface detonation monitoring and reservoir stimulation.

58 GEOSCIENCES↗
DOE OSTI2025

Predicting Flow in Fracture Networks With Quantum Algorithms

Uncertainty quantification plays a crucial role in the modeling of subsurface flow. For instance, uncertainties in the properties of geologic fracture networks significantly impact flow, requiring numerous simulations to accurately estimate quantities of interest. However, each simulation is computationally expensive because it requires solving a large linear system to capture features that involve both small and large fractures. An example is in percolation, where the interaction of many small fractures (which cumulatively can have a large surface area) with the rock matrix must be modeled precisely. Quantum computing is an emerging tool with the potential to address this issue. Quantum algorithms offer a significant speedup in solving linear systems, achieving efficiencies that are challenging to match with classical approaches. These classical approaches include direct solvers, such as LU decomposition, and iterative methods, notably preconditioned conjugate gradient, commonly used in subsurface modeling to solve large sparse systems. However, applying quantum algorithms to geologic fracture flow requires careful attention to algorithmic and problem-specific constraints to fully realize this quantum advantage. In this work we describe a quantum algorithm for generalized Monte Carlo applications with a quadratic speedup over the classical approaches which can be combined with the quantum speedup, currently under investigation, for solving quantum linear systems for subsurface flow. We show that for quantum algorithms the computational cost of estimating a quantity of interest for a statistical ensemble of networks is roughly the same as that of a single realization, essentially implying that one can get uncertainty quantification for free.

58 GEOSCIENCES↗
DOE OSTI2020

Morphological and nanomechanical changes in tungsten in high heat flux conditions

Abstract Morphological and nanomechanical alteration of tungsten in extreme environments, like those in edge localized modes in nuclear fusion environments, up to 46.3 GWm −2 heat fluxes were experimentally simulated using electrothermal plasma. Surface and subsurface damage to the tungsten is seen mainly in the form of pore formation, cracks, and resolidified melt instabilities. Mirco voids, rosette-type microfeatures, core-shell structure, particle enrichment, and submicron channels all manifest in the damaged subsurface. The formation of voids in the subsurface was determined to originate from the ductile fracture of hot tungsten by plastic flow but not developed to cracking. The voids were preferentially settled in grain boundaries, interfaces. The directionality of elongated voids and grains is biased to the heat flow vector or plasma pathway, which is the likely consequence of the thermally driven grain growth and sliding in the high-temperature conditions. The presence of a border between the transient layer and heat-affected zone is observed and attributed to plasma shock and thermal spallation of fractural tungsten at high temperature. Plasma peening-like hardening effects in tungsten were observed in the range of 22.7–46.3 GWm −2 but least in the case of the lowest heat flux, 12.5 GWm −2 .

36 MATERIALS SCIENCE↗
DOE OSTI2020

Mineral Fabric as a Hidden Variable in Fracture Formation in Layered Media

Two longstanding goals in subsurface science are to induce fractures with a desired geometry and to adaptively control the interstitial geometry of existing fractures in response to changing subsurface conditions. Here, we demonstrate that microscopic mineral fabric and structure interact with macroscopic strain fields to generate emergent meso-scale geometries of induced fractures. These geometries define preferential directions of flow. Using additively manufactured rock, we demonstrate that highly conductive flow paths can be formed in tensile fractures by creating corrugated surfaces. Generation, suppression and enhancement of corrugations depend on the relative orientation between mineral fabric and layering. These insights into the role of micro-scale structure on macro-scale flow provide a new method for designing subsurface strategies to maximize potential production or to inhibit flow.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Classification of computed thermal tomography images with deep learning convolutional neural network

Thermal tomography (TT) is a computational method for the reconstruction of depth profile of the internal material defects from Pulsed Infrared Thermography (PIT) nondestructive evaluation. Here, the PIT method consists of recording material surface temperature transients with a fast frame infrared camera, following thermal pulse deposition on the material surface with a flashlamp and heat diffusion into material bulk. TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of the subsurface internal defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to the heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify the size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. The performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shapes imported from scanning electron microscopy images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on the TT images of elliptical defects is capable of classifying the shape and orientation of irregular defects.

42 ENGINEERING↗
DOE OSTI2025

Oscillatory redox behavior in oxides: Cyclic surface reconstruction and reactivity modulation via the Mars–van Krevelen mechanism

The breaking of translational symmetry at oxide surfaces gives rise to coordinatively unsaturated cations/anions and surface restructuring—key factors that govern surface reactivity. Using direct in situ environmental transmission electron microscopy (TEM) observations along with atomistic modeling, we report oscillatory redox behavior in CuO under H 2 , where cyclic surface reconstruction and reactivity modulation occur via the Mars–van Krevelen (MvK) mechanism. We observe self-switching between oxygen-rich and oxygen-deficient surface reconstructions, alternately activating and deactivating the surface for H 2 O formation. During periods of chemical inactivity, the oxygen-deficient surface undergoes slow reoxidation via lattice oxygen diffusing from subsurface and bulk reservoirs, restoring the active oxygen-rich surface termination. The inherent disparity in chemical activity among undercoordinated surface ions, along with sluggish subsurface-to-surface oxygen replenishment, drives this oscillatory redox cycle, modulating H2-induced loss of lattice oxygen at the surface and its delayed replenishment from the subsurface. This creates spatiotemporally separated redox steps at the oxide surface. The phenomena and atomistic insights presented here have significant implications for manipulating the surface reactivity of oxides by tuning the separation of these redox steps.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Increasing freshwater and dissolved organic carbon flows to Northwest Alaska’s Elson lagoon

Manifestations of climate change in the Arctic are numerous and include hydrological cycle intensification and permafrost thaw, both expected as a result of atmospheric and surface warming. Across the terrestrial Arctic dissolved organic carbon (DOC) entrained in arctic rivers may be providing a carbon subsidy to coastal food webs. Yet, data from field sampling is too often of limited duration to confidently ascertain impacts of climate change on freshwater and DOC flows to coastal waters. This study applies numerical modeling to investigate trends in freshwater and DOC exports from land to Elson Lagoon in Northwest Alaska over the period 1981-2020. While the modeling approach has limitations, the results point to significant increases in freshwater and DOC exports to the lagoon over the past four decades. The model simulation reveals significant increases in surface, subsurface (suprapermafrost), and total freshwater exports. Significant increases are also noted in surface and subsurface DOC production and export, influenced by warming soils and associated active-layer thickening. The largest changes in subsurface components are noted in September, which has experienced a ~50% increase in DOC export emanating from suprapermafrost flow. Direct coastal suprapermafrost freshwater and DOC exports in late summer more than doubled between the first and last five years of the simulation period, with a large anomaly in September 2019 representing a more than fourfold increase over September direct coastal export during the early 1980s. These trends highlight the need for dedicated measurement programs that will enable improved understanding of climate change impacts on coastal zone processes in this data sparse region of Northwest Alaska.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Changes in soil water content and lateral flow exert large effects on soil thermal dynamics across Alaskan landscapes

Both lateral surface and subsurface water flow affect soil moisture dynamics, yet most land surface models only solve subsurface water movement vertically. Here, we use a 3D ecosystem model that considers both land surface and subsurface hydrologic processes to simulate soil moisture, which is then used to drive a 1-D vertical soil thermal model to simulate the soil moisture effects on soil thermal dynamics in central Alaska. Our coupled model improves soil temperature (ST) estimates by 43.5% in comparison with observational data. Soil moisture has little effect on ST during the wet season (-1.5%) and a substantial influence during the dry season (60%). Spatially, water lateral flow has significant impacts on both soil moisture and ST, causing model estimates for thawed areas in the transition season to increase by ~10% in the study area. Our results highlight the importance of considering dynamical soil moisture, as well as lateral flow effects, on soil thermal dynamics in permafrost regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Towards real-time monitoring: data assimilated time-lapse full waveform inversion for seismic velocity and uncertainty estimation

SUMMARY Rapid development of time-lapse seismic monitoring instrumentations has made it possible to collect dense time-lapse data for tomographically retrieving time-lapse (even continuous) images of subsurface changes. While traditional time-lapse full waveform inversion (TLFWI) algorithms are designed for sparse time-lapse surveys, they lack of effective temporal constraint on time-lapse data, and, more importantly, lack of the uncertainty estimation of the TLFWI results that is critical for further interpretation. Here, we propose a new data assimilation TLFWI method, using hierarchical matrix powered extended Kalman filter (HiEKF) to quantify the image uncertainty. Compared to existing Kalman filter algorithms, HiEKF allows to store and update a data-sparse representation of the cross-covariance matrices and propagate model errors without expensive operations involving covariance matrices. Hence, HiEKF is computationally efficient and applicable to 3-D TLFWI problems. Then, we reformulate TLFWI in the framework of HiEKF (termed hereafter as TLFWI-HiEKF) to predict time-lapse images of subsurface spatiotemporal velocity changes and simultaneously quantify the uncertainty of the inverted velocity changes over time. We demonstrate the validity and applicability of TLFWI–HiEKF with two realistic CO2 monitoring models derived from Frio-II and Cranfield CO2 injection sites, respectively. In both 2-D and 3-D examples, the inverted high-resolution time-lapse velocity results clearly reveal a continuous velocity reduction due to the injection of CO2. Moreover, the accuracy of the model is increasing over time by assimilating more time-lapse data while the standard deviation is decreasing over lapsed time. We expect TLFWI-HiEKF to be equipped with real-time seismic monitoring systems for continuously imaging the distribution of subsurface gas and fluids in the future large-scale CO2 sequestration experiments and reservoir management.

58 GEOSCIENCES↗
DOE OSTI2023

The influence of physical and algorithmic factors on simulated far-field waveforms and source–time functions of underground explosions using unsupervised machine learning

SUMMARY Characterizing explosion sources and differentiating between earthquake and underground explosions using distributed seismic networks becomes non-trivial when explosions are detonated in cavities or heterogeneous ground material. Moreover, there is little understanding of how changes in subsurface physical properties affect the far-field waveforms we record and use to infer information about the source. Simulations of underground explosions and the resultant ground motions can be a powerful tool to systematically explore how different subsurface properties affect far-field waveform features, but there are added variables that arise from how we choose to model the explosions that can confound interpretation. To assess how both subsurface properties and algorithmic choices affect the seismic wavefield and the estimated source functions, we ran a series of 2-D axisymmetric non-linear numerical explosion experiments and wave propagation simulations that explore a wide array of parameters. We then inverted the synthetic far-field waveform data using a linear inversion scheme to estimate source–time functions (STFs) for each simulation case. We applied principal component analysis (PCA), an unsupervised machine learning method, to both the far-field waveforms and STFs to identify the most important factors that control variance in the waveform data and differences between cases. For the far-field waveforms, the largest variance occurs in the shallower radial receiver channels in the 0–50 Hz frequency band. For the STFs, both peak amplitude and rise times across different frequencies contribute to the variance. We find that the ground equation of state (i.e. lithology and rheology) and the explosion emplacement conditions (i.e. tamped versus cavity) have the greatest effect on the variance of the far-field waveforms and STFs, with the ground yield strength and fracture pressure being secondary factors. Differences in the PCA results between the far-field waveforms and STFs could possibly be due to near-field non-linearities of the source that are not accounted for in the estimation of STFs and could be associated with yield strength, fracture pressure, cavity radius and cavity shape parameters. Other algorithmic parameters are found to be less important and cause less variance in both the far-field waveforms and STFs, meaning algorithmic choices in how we model explosions are less important, which is encouraging for the further use of explosion simulations to study how physical Earth properties affect seismic waveform features and estimated STFs.

58 GEOSCIENCES↗
DOE OSTI2024

Molecular mechanisms and environmental adaptations of flagellar loss and biofilm growth of Rhodanobacter under environmental stress

Biofilms aid bacterial adhesion to surfaces via direct and indirect mechanisms, and formation of biofilms is considered as an important strategy for adaptation and survival in suboptimal environmental conditions. However, the molecular underpinnings of biofilm formation in subsurface sediment/groundwater ecosystems where microorganisms often experience fluctuations in nutrient input, pH, and nitrate or metal concentrations are underexplored. Here, we examined biofilm formation under different nutrient, pH, metal, and nitrate regimens of 16 Rhodanobacter strains isolated from subsurface groundwater wells spanning diverse levels of pH (3.5 to 5) and nitrates (13.7 to 146 mM). Eight Rhodanobacter strains demonstrated significant biofilm growth under low pH, suggesting adaptations for survival and growth at low pH. Biofilms were intensified under aluminum stress, particularly in strains possessing fewer genetic traits associated with biofilm formation, findings warranting further investigation. Through random barcode transposon-site sequencing (RB-TnSeq), proteomics, use of specific mutants, and transmission electron microscopy analysis, we discovered flagellar loss under aluminum stress, indicating a potential relationship between motility, metal tolerance, and biofilm growth. Comparative genomic analyses revealed the absence of flagella and chemotaxis genes and the presence of a putative type VI secretion system in the highly biofilm-forming strain FW021-MT20. In this study we identified genetic determinants associated with biofilm growth under metal stress in a predominant environmental genus, Rhodanobacter, and identified traits aiding survival and adaptation to contaminated subsurface environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Quantitative surface studies of moiré intercalated Pb structures under Gr/SiC

Quantitative growth studies using surface diffraction and scanning tunneling microscopy are carried out to determine the intercalation conditions for Pb under Gr/SiC, with initial phase a mixture of buffer-layer and single-layer graphene. Intercalation is a kinetically complex, multistage process with intercalated Pb moving between different subsurface locations with annealing, eventually to the location of higher stability. The transfer is determined by monitoring the difference of a given spot intensity from its clean value, as a function of growth parameters. In addition, a broad, low-intensity (10×10) gr moiré phase is observed exclusively originating from intercalated Pb. Well-defined growth conditions are identified for the moiré spot to be observed reversibly. The (10×10) gr phase follows changes of the Pb(10) spot during growth and annealing experiments, instead of changes of the other Gr/SiC spots indicating preferred nucleation of Pb islands on the (10×10) gr domains. These structural results are discussed in connection to different models proposed for the (10×10) gr supercell and the subsurface Pb coverage. In conclusion, mass transport of subsurface Pb is unusually high, possibly because of the very high compression of the intercalated Pb, when compared to metallic Pb(111).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Design of a Two-Body Wave Energy Converter Featuring Controllable Geometry

While the field of wave energy has been the subject of numerical simulation, scale model testing, and precommercial project testing for decades, wave energy technologies remain in the early stages of development and must continue to prove themselves as a promising modern renewable energy field. A wave energy converter (WEC) concept currently being explored is the variable-geometry WEC (VGWEC), which aims to add an extra control option to WEC design. VGWECs attempt to incorporate controllable geometric features to adjust the floating body hydrodynamics to favor either power absorption, load shedding, or other operational goals. These variable geometry components have been proposed to be controlled on a sea-state-to-sea-state or wave-to-wave time scale depending on the force (or torque) and bandwidth limitations of the actuators required to manipulate just the controllable geometric hull features. Having control over both the WEC geometry components and the power takeoff (PTO) offers the potential to improve overall system performance and reliability if a cost-effective solution can be found for a given WEC architecture. This paper will present the recent developments and results of a VGWEC concept that incorporates variable-geometry modules into a two-body WEC. In the proposed VGWEC concept, the variable-geometry modules consist of air-inflatable bags in the surface float and a water inflatable ring in the subsurface body. The surface float is tethered directly to the subsurface body through tether lines, each connected to a separate PTO. Adjusting the geometry of both the surface and subsurface bodies along with the PTO coefficients can maximize power in design sea states while reducing motion response and PTO forces when transitioning to sea states where rated power is reached and load shedding is prioritized. The ability to transition between operating condition is expected to increase the sea state operational map and power capacity.

geometry control↗
DOE OSTI2024

Jackson, L., Johnson, M.B., Latrach, A., Grimes, D., Martinez, C., and Mclaughlin, J.F., 2024, Multidisciplinary geotechnical data collection, curation, and analysis for conformity with the regulatory framework for geologic carbon storage in Wyoming, USA: Geological Society of America Abstracts with Programs. Vol. 56, No. 5, 2024, doi: 10.1130/abs/2024AM-405024

Title: Multidisciplinary Geotechnical Data Collection, Curation, and Analysis for Conformity with the Regulatory Framework for Geologic Carbon Storage in Wyoming, USA. Text: Construction and operation of wells for geologic sequestration of carbon dioxide necessitate that they are permitted under the Environmental Protection Agency’s Underground Injection Control Class VI requirements. Class VI wells conform to stringent requirements to ensure long-term safety and integrity of the storage site and the protection of Underground Sources of Drinking Water. Entities pursuing Class VI permitting must provide comprehensive geologic site characterization, including regional geologic structure and stratigraphy, aquifer information, reservoir and confining unit geomechanical properties, geochemical analyses, assessment of trapping capacity and mechanisms, and a variety of other of multidisciplinary geotechnical data. The Wyoming Class VI Site Characterization Database Project is focused on developing a geologic site characterization database of geotechnical information, which has been compiled and verified from established, public databases/entities and scientific literature to expedite Class VI permitting in Sweetwater County within the Greater Green River Basin of southern Wyoming. The preliminary suite of compiled data from 14,000 wells includes 8,000 wells with logs and 7,250 wells with formation tops, ~70 wells with core data (e.g., X-Ray diffraction, petrographic, and petrophysical data), ~2,500 water analyses, ~740 seismic events data, and ~520 bottom-hole temperature measurements. Future work on—and stemming from—this project will include new core analyses, calculation and interpolation of subsurface temperature gradients, mechanical earth models, geochemical simulations, storage capacity estimation, stratigraphic column generation and correlation, and construction of subsurface maps. Finally, this work will help to inspire and facilitate subsurface data compilation and curation beyond Sweetwater County, Wyoming.

42 ENGINEERING↗
DOE OSTI2022

pnnl/dream_v3

The Designs for Risk Evaluation and Management (DREAM) tool was developed as part of the effort to quantify the risk of geologic storage of carbon dioxide (CO2) under the U.S. Department of Energy’s National Risk Assessment Partnership (NRAP). DREAM is an optimization tool created to identify optimal monitoring schemes that minimize the time to first detection of CO2 leakage from a subsurface storage formation. DREAM acts as a post-processer on user-provided output from subsurface leakage simulations. While DREAM was developed for CO2 leakage scenarios, it is applicable to any subsurface leakage simulation of the same output format

Kupis, Shyla↗
DOE OSTI2023

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↗
DOE OSTI2021

Biogeochemical dynamics and microbial community development under sulfate- and iron-reducing conditions based on electron shuttle amendment

Iron reduction and sulfate reduction are two of the major biogeochemical processes that occur in anoxic sediments. Microbes that catalyze these reactions are therefore some of the most abundant organisms in the subsurface, and some of the most important. Due to the variety of mechanisms that microbes employ to derive energy from these reactions, including the use of soluble electron shuttles, the dynamics between iron- and sulfate-reducing populations under changing biogeochemical conditions still elude complete characterization. Here, we amended experimental bioreactors comprised of freshwater aquifer sediment with ferric iron, sulfate, acetate, and the model electron shuttle AQDS (9,10-anthraquinone-2,6-disulfonate) and monitored both the changing redox conditions as well as changes in the microbial community over time. The addition of the electron shuttle AQDS did increase the initial rate of Fe III reduction; however, it had little effect on the composition of the microbial community. Our results show that in both AQDS- and AQDS+ systems there was an initial dominance of organisms classified as Geobacter (a genus of dissimilatory Fe III -reducing bacteria), after which sequences classified as Desulfosporosinus (a genus of dissimilatory sulfate-reducing bacteria) came to dominate both experimental systems. Furthermore, most of the ferric iron reduction occurred under this later, ostensibly “sulfate-reducing” phase of the experiment. This calls into question the usefulness of classifying subsurface sediments by the dominant microbial process alone because of their interrelated biogeochemical consequences. To better inform models of microbially-catalyzed subsurface processes, such interactions must be more thoroughly understood under a broad range of conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Model simulations of Plum Island Ecosystems LTER low marsh site using ELM-PFLOTRAN

Model simulations using the E3SM Land Model (ELM) coupled to the PFLOTRAN reactive transport model via the Alquimia interface. The simulations were conducted for a tidal salt marsh at the Plum Island Ecosystems LTER near Rowley, Massachusetts, USA. Model simulations were forced using site-specific tidal cycles and salinity, and the simulations used a biogeochemical reaction network including aerobic decomposition, sulfate reduction, iron reduction, and methanogenesis. Model outputs include simulated carbon stocks, carbon dioxide and methane fluxes, and porewater concentrations of key solutes related to sulfur, iron, and carbon cycling. The model simulations included a saline simulation (with tidal sulfate inputs), a fresh simulation (with low salinity and low sulfate inputs), and a saline simulation with lower vegetation productivity to represent the effect of salinity on vegetation. These simulations were conducted to demonstrate that a new model framework incorporating subsurface redox and biogeochemical interactions into a land surface model could reproduce measured surface greenhouse gas fluxes and biogeochemical dynamics in tidal marsh ecosystems, and to test whether including redox interactions in a land surface model would allow the model to resolve contrasts in biogeochemical cycling and greenhouse gas production between saline and freshwater wetlands.The data package includes gzipped tar archives (which can be expanded using standard tar and gzip utilities) of model outputs from three model configurations: saline subsurface and reduced vegetation productivity related to salinity; saline subsurface with vegetation productivity not reduced; and freshwater. Also included are code for the modified E3SM model, Alquimia interface, and PFLOTRAN reactive transport simulator in gzipped tar format; plain text parameter and configuration files; python code files for visualizing model output and defining model configurations; and model output, tide and salinity forcing, and configuration files in netCDF format. See the README.md file in the data package for a detailed description of all files contained in the package. All files are in netCDF (.nc), gzipped tar archive (.tar.gz or .tgz), or text (all other files).Updated: May 13, 2024. Model output, E3SM code, PFLOTRAN input files, and python codes for visualizing results were updated to reflect changes made for the manuscript revision. The updated archive reflects the code and model output from the final accepted manuscript. Changes included updated reaction parameters reflecting improved parameterization and additional comparisons with field measurements. E3SM code changes included better support for multiple grid cells and improved flow and transport parameterization.

54 ENVIRONMENTAL SCIENCES↗