Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Study”

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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Experimental and Theoretical Studies of the Surface Oxidation Process of Rare–Earth Tritellurides

Recent studies have established Van der Waals (vdW) layered and 2D rare-earth tritellurides (RTe 3 ) as superconductors and near room-temperature charge density wave (CDW) materials. Their environmental stability raises natural concern owing to aging/stability effects observed in other tellurium-based layered crystals. Here, the results establish the stability and environmental aging characteristics of these RTe 3 systems involving a variety of metals such as La, Nd, Sm, Gd, Dy, and Ho. The atomic force microscopy (AFM) and scanning electron microscopy (SEM) results show that all the RTe 3 sheets oxidize to form thin TeO x layers that are primarily confined to the surface, edges, and grain boundaries. Time-resolved in situ Raman spectroscopy measurements are used to understand the kinetics of the oxidization process for different lanthanide metal cations and establish their relative stability/resilience to oxidization. Overall results indicate that the vdW layers show higher air stability as the 4f electron number decreases going from Ho to La, resulting in the most stable LaTe 3 compared to the least stable HoTe 3 . Comprehensive quantum mechanical simulations reveal that environmental degradation originates from a strong oxidizing reaction with O 2 molecules, while humidity (H 2 O) plays a negligible role unless Te vacancies are present. Moreover, the simulations explain the effects of 4f electrons on the work function and Te vacancies formation, which directly impact the aging characteristics of RTe 3 layers. Interestingly, optical and electrical measurements show that the CDW response is still observed in aged RTe 3 layers owing to the presence of underlying pristine/nonoxidized RTe 3 layers, except CDW transition temperatures increase due to the thickness effect. Overall results offer the first in-depth environmental aging studies on these materials, which can be applied to engineer and design their chemical stability, surface properties, and overall CDW characteristics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Toward More Efficient Organic Solar Cells: A Detailed Study of Loss Pathway and Its Impact on Overall Device Performance in Low‐Offset Organic Solar Cells

Abstract Low‐offset organic solar cell systems have attracted great interest since nonfullerene acceptors came into the picture. While numerous studies have focused on the charge generation process in these low‐offset systems, only a few studies have focused on the details of each loss channel in the charge generation process and their impact on the overall device performance. Here, several nonfullerene acceptors are blended with the same polymer donor to form a series of low‐offset organic solar cell systems where significant variation in device performance is observed. Through detailed analyses of loss pathways, it is found that: i) the donor:acceptor interfaces of PM6:Y6 and PM6:TPT10 are close to the optimum energetic condition, ii) energetics at the donor:acceptor interface are the most important factor to the overall device performance, iii) exciton dissociation yield can be field‐dependent owing to the sufficiently small energetic offset at the donor:acceptor interface, and iv) the change in substituents in the terminal group of Y‐series acceptors in this work mainly affects energetics at the donor:acceptor interface instead of the interface density in the active layer. In general, this work presents a path toward more efficient organic solar cells.

14 SOLAR ENERGY↗
DOE OSTI2023

The Role of Transition Metals on Chemo-Mechanical Instabilities in Prussian Blue Analogues For K-Ion Batteries: The Case Study on KNHCF Versus KMHCF

Prussian blue analogues (PBAs) cathodes can host diverse monovalent and multivalent metal ions due to their tunable structure. However, their electrochemical performance suffers from poor cycle life associated with chemo-mechanical instabilities. This study investigates the driving forces behind chemo-mechanical instabilities in Ni- and Mn-based PBAs cathodes for K-ion batteries by combining electrochemical analysis, digital image correlation, and spectroscopy techniques. Capacity retention in Ni-based PBA is 96% whereas it is 91.5% for Mn-based PBA after 100 cycles at C/5 rate. During charge, the potassium nickel hexacyanoferrate (KNHCF) electrode experiences a positive strain generation whereas the potassium manganese hexacyanoferrate (KMHCF) electrode undergoes initially positive strain generation followed by a reduction in strains at a higher state of charge. Overall, both cathodes undergo similar reversible electrochemical strains in each charge–discharge cycle. There is ~0.80% irreversible strain generation in both cathodes after 5 cycles. XPS studies indicated richer organic layer compounds in the cathode-electrolyte interface (CEI) layer formed on KMHCF cathodes compared to the KNHCF ones. Faster capacity fades in Mn-based PBA, compared to Ni-based ones, is attributed to the formation of richer organic compounds in CEI layers, rather than mechanical deformations. In conclusion, understanding the driving forces behind instabilities provides a guideline to develop material-based strategies for better electrochemical performance.

25 ENERGY STORAGE↗
DOE OSTI2024

A Comprehensive Experimental Study on Microstructure‐Graded Graphite Anodes for Enhancing Fast‐Charging Capability of Lithium‐Ion Batteries

Lithium‐ion batteries with high gravimetric capacity density and improved cycle life performance under fast‐charging conditions are crucial for widespread electric vehicle (EV) adoption. This study investigates how designing graphite anode microstructure, specifically porosity, and particle‐size gradients, improves lithium‐ion (Li + ) transport during fast‐charging conditions. Three‐layered graphite anodes with varying porosity (24%, 36%, 46%) and particle size gradients (3, 5, 10 μm) were compared to a conventional single‐layered electrode in half‐cell configurations. At room temperature and high discharge rate (2C), both gradient structures showed significantly enhanced capacity retention (80% and 67% vs. 50%) compared to the conventional electrode, highlighting the effectiveness of microstructure engineering for fast charging. The study also investigated the temperature's impact on cycle life. After 200 cycles at 2°C and 45°C, all gradient structures demonstrated superior capacity retention (≈80%) compared to the conventional electrode (35%), suggesting the gradients mitigate degradation rate at high temperatures. Electrochemical impedance spectroscopy confirmed superior Li+ diffusion and lower resistivity in gradient electrodes. Simulations explored the influence of gradient profiles on reaction kinetics across the electrode thickness. Overall, this research demonstrates that the fast‐charging capability of graphite electrodes can be greatly enhanced by engineering the electrode microstructure, thereby making EV technology more accessible and appealing.

Ahmadi, Soma↗
DOE OSTI2026

A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design

We present a benchmarking study of active learning (AL) schemes for designing planar multilayer nanophotonic metamaterials, where the design tasks are formulated as binary optimization problems. Different surrogate models, including factorization machine (FM), Gaussian process regression (GPR), and convolutional neural network (CNN), combined with different optimization methods, including exhaustive enumeration, discrete particle swarm optimization (DPSO), quantum annealing (QA), hybrid QA, and simulated annealing are studied. The benchmark cases investigated range from small problems with short binary lengths (N = 25) to large problems with N up to 100, focusing on the design of two classes of photonic structures, including antireflective coatings for the long-wavelength infrared region and transparent radiative coolers. For small problems, CNN coupled with DPSO in AL achieves the best performance. As N increases, FM with QA outperforms GPR and CNN. For FM-based AL, hybrid QA yields the best optimization results, particularly in high-dimensional cases (N = 100). These results demonstrate that the optimization method can significantly affect in AL performance as N increases, and that QA-based optimization can provide practical routes for mitigating the optimization bottleneck in high-dimensional problems.

Jung, Serang [Kyung Hee University, Korea]↗
DOE OSTI2020

Estimating rates and patterns of diversification with incomplete sampling: a case study in the rosids

Premise Recent advances in generating large‐scale phylogenies enable broad‐scale estimation of species diversification. These now common approaches typically are characterized by (1) incomplete species coverage without explicit sampling methodologies and/or (2) sparse backbone representation, and usually rely on presumed phylogenetic placements to account for species without molecular data. We used empirical examples to examine the effects of incomplete sampling on diversification estimation and provide constructive suggestions to ecologists and evolutionary biologists based on those results. Methods We used a supermatrix for rosids and one well‐sampled subclade (Cucurbitaceae) as empirical case studies. We compared results using these large phylogenies with those based on a previously inferred, smaller supermatrix and on a synthetic tree resource with complete taxonomic coverage. Finally, we simulated random and representative taxon sampling and explored the impact of sampling on three commonly used methods, both parametric (RPANDA and BAMM) and semiparametric (DR). Results We found that the impact of sampling on diversification estimates was idiosyncratic and often strong. Compared to full empirical sampling, representative and random sampling schemes either depressed or inflated speciation rates, depending on methods and sampling schemes. No method was entirely robust to poor sampling, but BAMM was least sensitive to moderate levels of missing taxa. Conclusions We suggest caution against uncritical modeling of missing taxa using taxonomic data for poorly sampled trees and in the use of summary backbone trees and other data sets with high representative bias, and we stress the importance of explicit sampling methodologies in macroevolutionary studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Biorefinery siting and sizing to achieve the US Billion‐Ton Bioeconomy vision: A case study using a gasification–Fischer–Tropsch process

Achieving a secure, abundant, and affordable energy future requires a robust and adaptable energy strategy, with bioenergy playing a pivotal role. Biomass-based energy presents a promising pathway to use domestic resources while fostering economic opportunities in rural areas. Despite the potential to source more than 1 billion dry short tons of biomass annually in the US, significant infrastructure and economic barriers hinder full utilization for energy production. This study used the Biofuel Infrastructure, Logistics, and Transportation (BILT) model to assess biorefinery siting and scale and determine the number and size of facilities required to maximize use of the US biomass potential. A spatially agnostic approach first assessed the effects of facility capacity and transportation constraints on biomass use. Then, a spatially explicit analysis integrated county-level biomass availability from the US Department of Energy's 2023 Billion-Ton Report and technoeconomic assessments to evaluate different biorefinery deployment scenarios. The results indicate that an optimized mix of facility sizes is essential to leverage biomass resources fully across varying regional production densities to maximize use of the US biomass potential. Larger biorefineries or co-located smaller facilities significantly enhance biomass use while reducing costs through economies of scale. These findings underscore the importance of strategically balancing facility capacity and spatial distribution to optimize the bioenergy supply chain. In conclusion, this study provides critical insights for advancing the US bioenergy economy by aligning biorefinery deployment with biomass resource availability and economic viability.

BILT Model↗
DOE OSTI2020

Global functional connectivity density alterations in patients with bipolar disorder with auditory verbal hallucinations and modest short‐term effects of transcranial direct current stimulation augmentation treatment—Baseline and follow‐up study

Abstract Objectives To investigate the neuroimaging characteristics of auditory verbal hallucinations (AVHs) in patients with bipolar disorder (BP) experiencing depressive episodes with and without AVHs, and alterations in those characteristics after transcranial direct current stimulation (tDCS). Methods For a baseline pilot study, we recruited 80 patients with BP and depressive status (40 with and 40 without AVHs), and 40 healthy controls (HCs). Their global functional connectivity density (gFCD) was screened by functional magnetic resonance imaging (fMRI). Voxel‐wise one‐way analysis of covariance (ANCOVA) was conducted to detect intergroup differences in gFCD. In a follow‐up study, the effects of 5 weeks of tDCS augmentation treatment on clinical symptoms and gFCD were assessed in the 40 BP patients with AVHs. Results Compared to HCs, BP patients with and without AVHs exhibited increased gFCD in the central parietal lobe, insular lobe, and middle cingulate cortex, with decreased gFCD in the posterior parietal cortex, lateral prefrontal cortex, and occipital lobe (all bilateral). Only patients with AVHs showed increased gFCD in the Broca and Wernicke regions, and decreased gFCD in the hippocampus (all bilateral). After 5 weeks of tDCS, AVHs were slightly alleviated and gFCD abnormalities in the hippocampus were mildly attenuated. Conclusions Patients with BP and AVHs showed disturbances in the brain's communication capacity mainly in the left frontoparietal network, control network, and memory circuitry. Five weeks of tDCS alleviated AVHs slightly, without improving depressive symptoms, and attenuated hippocampal gFCD alterations in these patients.

Zhuo, Chuanjun↗
DOE OSTI2023

The α-WC(0001) Surface as a Hydrogen Sponge: A First Principle Study of H 2 Dissociation and Formation of Low and High Coverages

Tungsten carbide (WC) displays a Pt-like behavior in catalysis, applied in hydrogenation processes. Numerous theoretical studies have modeled the behavior and use of adsorbed hydrogen without obtaining a general picture, missing basic links between H 2 dissociation and generation of high surface coverage (Θ H >0.5 ML). Here, in this study, the capability of C- and W-terminations of the α-WC(0001) surface is analyzed to dissociate several H 2 molecules to produce coverages, Θ H , ranging from low to very high values (0.13<Θ H <2.00 ML). Density functional theory and an ab initio atomistic thermodynamic were used to achieve the conditions for H 2 dissociation. The WC–C surface has higher capacity to dissociate H 2 molecules than WC–W. However, both surfaces can reach full surface coverage, Θ H =1 ML, at mild ambient conditions, T=300 K and P=1 atm, and even up to 500 K at low and high pressures. The H-adatoms on WC–W are more labile than on WC–C. The binding of adsorbates is hindered at high Θ H , implying a need to modulate Θ H according to the application. The results give the basis to understand the capabilities of WC-based catalysts in hydrogenation-related reactions, with the advantage of WC being a hydrogen reservoir at mild practical catalytic conditions.

03 NATURAL GAS↗
DOE OSTI2025

Developing Digital Twin Visualizations: A Methodology and Case Study on Chemical Separation Processing

As advances in digital engineering continue to push the technological boundaries, digital twin (DT) visualizations for diagnostics and safeguards advancement become much more feasible and practical. DTs generate large and complex data streams that require effective user interfaces to provide monitoring and diagnostic capabilities. Unfortunately, while these frameworks exist, there is not much research on the systematic documentation of human–computer interaction (HCI) for DT visualization. This work presents a dual-mode visualization methodology (two dimensional [2D] graphical user interface dashboard and 3D mixed reality) designed to support diagnostic tasks in DT systems and building on a validated framework and applying established HCI principles. The methodology is demonstrated through a case study of aqueous processing at Idaho National Laboratory, using experimental data from the chemical solvent extraction runs. Our interfaces display real-time alerts and monitoring to inform users of safeguards anomalies. The interfaces use immersive 3D mixed-reality visualization for further system and experiment investigation. This work demonstrates how the systematic application of HCI principles can inform DT visualization design for diagnostic and safeguards applications. While formal user evaluation studies remain as future work, this paper documents the systematic design methodology and demonstrates a proof-of-concept implementation.

3D visualization↗
DOE OSTI2020

Influence of Metal-Alkyls on Early-Stage Ethylene Polymerization over a Cr/SiO 2 Phillips Catalyst: A Bulk Characterization and X-ray Chemical Imaging Study

The Cr/SiO 2 Phillips catalyst has taken a central role in ethylene polymerization since its invention in 1953. The uniqueness of this catalyst is related to its ability to produce broad molecular weight distribution (MWD) PE materials as well as that no co-catalysts are required to attain activity. Nonetheless, co-catalysts in the form of metal-alkyls can be added for scavenging poisons, enhancing catalyst activity, reducing the induction period, and tailoring polymer characteristics. The activation mechanism and related polymerization mechanism remain elusive, despite extensive industrial and academic research. Here, we show that by varying the type and amount of metal-alkyl co-catalyst, we can tailor polymer properties around a single Cr/SiO 2 Phillips catalyst formulation. Furthermore, we show that these different polymer properties exist in the early stages of polymerization. We have used conventional polymer characterization techniques, such as size exclusion chromatography (SEC) and 13 C NMR, for studying the metal-alkyl co-catalyst effect on short-chain branching (SCB), long-chain branching (LCB) and molecular weight distribution (MWD) at the bulk scale. In addition, scanning transmission X-ray microscopy (STXM) was used as a synchrotron technique to study the PE formation in the early stages: allowing us to investigate the produced type of early-stage PE within one particle cross-section with high energy resolution and nanometer scale spatial resolution.

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

Mechanistic Insights into the Demethylation of Lignin‐Derived Structures Using Protic Ionic Liquids: A Density Functional Theory Study

Lignin valorization is restricted by the stability of its methoxy groups, creating a critical need for efficient demethylation strategies. Here, in this study, density functional theory (DFT) is employed to dissect the mechanistic pathways of demethylation in lignin model compounds, guaiacol and syringol, using protic ionic liquids (PILs) that act as both solvent and catalyst. Conductor‐like Screening Model for Real Solvents (COSMO‐RS) analysis identifies monoethanolammonium acetate ([MEOA][Ace]) as the most promising medium, attributed to its strong hydrogen bonding network and solvation ability. By integrating implicit and explicit solvation models, it is revealed that an acid‐catalyzed hydrolytic mechanism governs demethylation, with PILs stabilizing crucial transition states and intermediates. Complementary electronic structure evaluations, including highest occupied molecular orbital–lowest unoccupied molecular orbital (HOMO‐LUMO) gap analysis, charge distribution, and electrostatic potential mapping, demonstrate how PILs lower energetic barriers and enhance reactivity. To simulate realistic environments, this study is extended to lignin dimer complexes with varying water content, uncovering how water‐bridged solvation reverses demethylation preference from guaiacyl to syringyl units. This mechanistic shift aligns with experimental observations showing faster S‐unit reactivity in hydrated systems. Together, these findings provide atomic‐level insight into lignin demethylation dynamics and highlight how tuning acid concentration in PILs can accelerate kinetics, enabling a rational pathway toward next‐generation biomass conversion technologies.

COSMO-RS↗
DOE OSTI2022

Model‐Based Approach to Selecting Pegfilgrastim Dose for Pharmacokinetic and Pharmacodynamic Similarity Studies in Biosimilar Development

This study applied modeling and simulation (M&S) approaches to evaluate the sensitivity of pegfilgrastim pharmacokinetics (PKs) and pharmacodynamics (PDs) to changes in dose amount, and linear or nonlinear clearance (CL) over pegfilgrastim subcutaneous dose of 2–6 mg. A previously published model was adapted to better describe pegfilgrastim PK and PD data in healthy subjects and used in simulation. Nonlinear CL accounts for 98% and 77%, respectively, of the total CL of pegfilgrastim at 2 and 6 mg. The sensitivity analyses showed: (i) PK of 2 and 6 mg doses are similarly sensitive to detect differences for a 5% change in dose; (ii) PK of 2 mg dose is more sensitive to changes in receptor binding affinity, a model parameter for nonlinear CL, and a product quality attribute characterized with orthogonal methods as part of demonstrating analytical similarity between products; (iii) PK of approved 6 mg dose is more sensitive to changes in linear CL, which has not been associated with any specific product quality attributes, and (iv) the PDs are not sensitive to changes in linear or nonlinear CL. Taken together, our analyses support that the approved pegfilgrastim dose of 6 mg is appropriate for detecting differences between a biosimilar and the reference products in pegfilgrastim PK and PD similarity studies. The described M&S approaches can be adopted to support dose selection for biosimilars with nonlinear PK and complex PK–PD interplay.

Pharmacology & Pharmacy↗
DOE OSTI2023

Novel Co 5 Cluster Based Triazole Bridged Cobalt-Fluorophosphate: Synthesis, Structure, Magnetic and Heterogeneous Catalytic Epoxidation Studies

A novel triazole bridged cobalt fluorophosphate coordination polymer with the formula {Co 5 (1,2,4-triazole) 2 (OH) 2 (PO 3 F) 4 } n has been synthesized. Single crystal X-ray studies reveal that the compound comprises of Co 5 clusters which ultimately build the whole framework, here all cobalt centers are in octahedral geometry established from continuous shape analysis. All the cobalt centers are in Co(II) oxidation state and the results are supported by the bond valence sum (BVS) calculation. The sample has been characterized by single crystal X-ray, powder X-ray, FTIR and TGA analysis. The compound was tested for olefin catalysis performance and magnetism. Magnetization measurements reveal overall antiferromagnetic interactions among the Co(II) ions. The compound is very active in the catalytic transformation of olefins to their corresponding epoxides. In conclusion, catalytic epoxidation studies reveal that cyclohexene and styrene can be converted up to 97% with almost 65% selectivity of products with higher TON numbers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Experimental and numerical studies of seismic fluid-structure interaction in a base-supported cylindrical vessel

Seismic design and qualification of advanced reactors will rely heavily on the use of verified and validated numerical models capable of capturing the interaction of the vessel, its contained fluid, and the internal equipment: fluid-structure interaction (FSI) analysis. Analytical solutions can be used for preliminary sizing and design of such vessels but their application is limited to simple geometries and boundary conditions, and small amplitude, translational (and rotational) inputs. To validate numerical models for seismic FSI analysis in finite element codes, a comprehensive set of experiments was performed on a liquid-filled cylindrical vessel, using a 6 degree-of-freedom earthquake simulator. Results in terms of sloshing frequency, damping ratio in sloshing modes, and hydrodynamic responses (wave height, hydrodynamic pressure, base shear, and base moment) for multi-directional earthquake simulator inputs are reported and compared with analytical solutions for liquid-filled vessels. The impact of seismic (base) isolation on hydrodynamic responses was studied using earthquake simulator inputs generated using a virtual isolation system. Data from the experiments are used to validate a numerical model of the fluid-filled vessel using the Arbitrary Lagrangian Eulerian (ALE) solver in the commercial finite element program LS-DYNA. Validation studies are presented for multi-directional seismic inputs, including rocking motions. Lagrangian modeling approaches using an elastic material formulation for the fluid are also investigated and their limitations and possible applications are identified. Here, the results are broadly applicable to the seismic response of base supported, liquid-filled vessels.

58 GEOSCIENCES↗
DOE OSTI2022

A machine learning approach to water quality forecasts and sensor network expansion: Case study in the Wabash River Basin, United States

Abstract Midwestern cities require forecasts of surface nitrate loads to bring additional treatment processes online or activate alternative water supplies. Concurrently, networks of nitrate monitoring stations are being deployed in river basins, co‐locating water quality observations with established stream gauges. However, tools to evaluate the future value of expanded networks to improve water quality forecasts remains challenging. Here, we construct a synthetic data set of stream discharge and nitrate for the Wabash River Basin—one of the United States’ most nutrient polluted basins—using the established Agro‐IBIS and THMB models. Synthetic data enables rapid, unbiased and low‐cost assessment of potential sensor placements to support management objectives, such as near‐term forecasting. Using the synthetic data, we established baseline 1‐day forecasts for surface water nitrate at 12 cities in the basin using support vector machine regression (SVMR; RMSE 0.48–3.3 ppm). Next, we used the SVMRs to evaluate the improvement in forecast performance associated with deployment of additional nitrate sensors. We identified the optimal sensor placement to improve forecasts at each city, and the relative value of sensors at each candidate location. Finally, we assessed the co‐benefit realized by other cities when a sensor is deployed to optimize a forecast at one city, finding significant positive externalities in all cases. Ultimately, our study explores the potential for machine learning to make near‐term predictions and critically evaluate the improvement realized by expanding a monitoring network. While we use nitrate pollution in the Wabash River Basin as a case study, this approach could be readily applied to any problem where the future value of sensors and network design are being evaluated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

River–aquifer interactions enhancing evapotranspiration in a semiarid riparian zone: A modelling study

The hydrologic flows across the river–aquifer interface play an important role in groundwater dynamics and biogeochemical reactions within the subsurface; however, little is known about the effects of river–aquifer interactions on land surface processes. In this study, we developed a fully coupled three-dimensional (3D) land surface and subsurface model at a high resolution (~1 km) that accounts for high-frequency hydrologic exchange flow conditions to investigate how river–aquifer interactions modulate surface water budgets in the Upper Columbia-Priest Rapids watershed, a typical semiarid watershed located in the northwestern United States where river stage fluctuates in response to reservoir releases changing. Our results show that the spatiotemporal dynamics of river–aquifer interactions are highly heterogeneous, driven mainly by river-stage fluctuations. Adding 6.64 × 10 6 m 3 year –1 of water over the watershed from the river to groundwater owing to the lateral flow, river–aquifer interactions led to an increase in soil evaporation and transpiration supplied by higher soil moisture content, particularly in deeper subsurface. In a hypothetic future scenarios where a 5-m rise in river stage was assumed, the hydrologic flow exchange rates were intensified, resulting in higher surface water over the entire watershed. Overall, lateral flow induced by river–aquifer exchanges leads to an increase in evapotranspiration of ~75% in the historical period and of ~83% in the hypothetical future scenario. Finally, our study demonstrates the potential of coupled model as an effective tool for understanding river–aquifer–land surface interactions, and indicates that river–aquifer interactions fundamentally alter the water balance of the riparian zone for the semiarid watershed and will likely become more frequent and intense in the future under the effects of climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Modelling the Effects of Wetland Restoration on Coastal Hydrology: A Case Study of Elkhorn Slough Watershed, California

ABSTRACT Coastal wetlands, some of the most productive ecosystems on Earth, provide critical ecosystem services, including support of biodiversity, carbon sequestration and flood protection. In recent decades, these ecosystems have experienced extensive coastal wetland loss. Coastal wetland restoration provides a beacon of hope, offering a chance to reclaim these important habitats. However, even with billions of dollars invested worldwide in restoring coastal wetlands, we still lack comprehensive knowledge about the effectiveness of these restoration efforts in recovering wetland ecosystem functions and how future climate change may affect these efforts. The ability to evaluate how these ecosystems will function in the future is vital for examining current investments and developing future protection and management plans. We selected Elkhorn Slough, a tidal estuary, in California, to investigate the impact of wetland restoration and sea level rise (SLR) on coastal hydrology using the process‐based coastal hydrologic model, Advanced Terrestrial Simulator (ATS), informed by site‐specific data. We designed a novel modelling workflow for incorporating wetland restoration features into land cover and soil properties for the model parameterization. The validation results demonstrate a strong agreement between modelled and observed data. We studied the characteristics of coastal watershed hydrology, then focused on the surface water dynamics at two wetland sites within Elkhorn Slough, a reference site and a restored site. Our simulation results indicate that the restored site successfully maintains surface elevation, resulting in reduced surface inundation. We also examined the impact of wetland restoration under expected SLR over the next few decades. The low‐lying Yampah Marsh, the reference site, is likely to be inundated due to future SLR when highest tides arrive, while a higher percentage of Hester Marsh, the restored site, would retain marsh vegetation in coming decades, regardless of tidal conditions. Our study provides important information for examining the outcome of restoration practices that include surface elevation in tidal wetlands under climate changes.

advanced terrestrial simulator↗