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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Extracting Vehicle Trajectories from Partially Overlapping Roadside Radar

This work presents a methodology for extracting vehicle trajectories from six partially-overlapping roadside radars through a signalized corridor. The methodology incorporates radar calibration, transformation to the Frenet space, Kalman filtering, short-term prediction, lane-classification, trajectory association, and a covariance intersection-based approach to track fusion. The resulting dataset contains 79,000 fused radar trajectories over a 26-h period, capturing diverse driving scenarios including signalized intersections, merging behavior, and a wide range of speeds. Compared to popular trajectory datasets such as NGSIM and highD, this dataset offers extended temporal coverage, a large number of vehicles, and varied driving conditions. The filtered leader–follower pairs from the dataset provide a substantial number of trajectories suitable for car-following model calibration. The framework and dataset presented in this work has the potential to be leveraged broadly in the study of advanced traffic management systems, autonomous vehicle decision-making, and traffic research.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Integrated Strategies for Overcoming Resolution Limits in Electron Beam Lithography of Chemically Amplified Resists

Electron beam lithography (EBL) of chemically amplified resists (CARs) faces fundamental challenges, including stochastic electron scattering and acid diffusion, that limit resolution and reproducibility. Using SU-8 as a model CAR, this study systematically investigated complementary strategies to address these challenges, combining multipass exposure, proximity effect correction (PEC) with midrange correction factors, base quencher incorporation, and post-exposure bake (PEB) suppression. Monte Carlo simulations and calibrated PEC modeling revealed that extending the point spread function to include a midrange scattering component significantly improved critical dimension (CD) control across varying pattern densities, correcting deviations that conventional two-term PEC failed to capture. Multipass exposure, particularly 4-pass writing with a 25% offset, redistributed the dose to average stochastic beam and scattering fluctuations, reducing line-width roughness by more than 50% and yielding more uniform nanoscale features. Photoacid confinement was investigated by adding urea as a base quencher, which successfully reduced acid diffusion but introduced substantial sensitivity penalties without improving ultimate resolution or Z-factor performance, underscoring the trade-offs of chemical versus physical confinement. Suppressing PEB most directly minimized acid diffusion, resulting in improved Z-factors and reproducible 30 nm half-pitch dense line/space patterns. Overall, these results demonstrated that PEC with midrange correction, multipass strategies, quencher additives, and PEB-free processing addresses different aspects of the EBL process window and that their integration provides a comprehensive framework for managing stochastic scattering, diffusion, and chemical amplification effects. This framework advances dense nanoscale patterning in CARs and establishes guiding principles for optimizing resist design and process strategies in high-resolution EBL and potentially other advanced lithographies, such as extreme ultraviolet (EUV) lithography.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Detect the Unobservable: Abnormality Detection in mixed Autonomy for Lane Change Maneuver with Following Vehicles’ Trajectories Only

Highly Automated Vehicles (HAVs) and Advanced Driver-Assistance Systems (ADAS) are transforming modern transportation with enhanced mobility, safety, and efficiency. Despite their advantages, cybersecurity vulnerabilities in these systems can lead to abnormal behavior, posing significant risks to surrounding human-driven vehicles (HDVs) in mixed traffic environments. Here, this article addresses the challenge of detecting abnormal lateral movements of HAVs/ADAS vehicles using only trajectory profiles of following HDVs. Specifically, we propose a novel modeling approach that captures both normal and abnormal lateral behaviors through vehicle kinematics, integrated decision-making processes, vehicle control using symbolic regression for lane change vehicles. Additionally, we introduce an abnormality detection framework that relies on observable HDV data, even in occlusion scenarios. The framework evaluates the sensitivity of various car-following models to detect abnormal behaviors, providing insights into the interaction between HAVs/ADAS and HDVs in mixed autonomy systems.

Connected and Automated vehicles↗
DOE OSTI2024

Zero Emission Cargo Transport (ZECT) II Demonstration: South Coast Air Quality Management District (Final Report)

The South Coast Air Quality Management District (South Coast AQMD), California Air Resources Board (CARB) and Southern California Association of Governments (SCAG) — the agencies responsible for preparing the State Implementation Plan required under the federal Clean Air Act — have agreed that attainment of federal air quality standards for the region will require a transition to the broad use of zero and near-zero emission energy sources in cars, trucks and other equipment. Accordingly, the 2012 South Coast AQMD Air Quality Management Plan, the SCAG 2012 Regional Transportation Plan, and the “Vision for Clean Air: A Framework for Air Quality and Climate Control Planning” all identify the need to immediately enact a phasing in of zero and near-zero emission technologies to meet air quality goals. In 2014, South Coast AQMD was awarded grant funding under the US Department of Energy Zero Emission Cargo Transport (ZECT) II Demonstration program to develop and demonstrate zero-emission drayage trucks for goods movement operations between the Port of Los Angeles (POLA) and Port of Long Beach (POLB) near dock rail yards and warehouses: 1) development and demonstration of zero-emission fuel cell range extended electric drayage trucks and 2) development and demonstration of hybrid electric drayage trucks. The purpose of this project was to accelerate deployment of zero emission cargo transport technologies to reduce harmful diesel emissions, petroleum consumption and greenhouse gases in the surrounding communities along the goods movement corridors that are impacted by heavy diesel traffic and the associated air pollution. Between 2014 – 2024, six ZECT II zero-emission fuel cell drayage truck platforms, including fuel cell range extended and CNG hybrid trucks, were successfully designed, developed, integrated, built, tested, and demonstrated with drayage fleet operators in transportation corridors within areas of the South Coast AQMD jurisdiction in Southern California such as in and around POLA and POLB. Portable hydrogen refueling was deployed to support the fuel cell vehicles. The project had real-time improvement with on-going debugging and optimizations while the vehicles were under demonstration. All platforms demonstrated sufficient or excess power, torque, and energy to support 82,000lbs Gross Vehicle Weight Rating and gradeability to perform their daily duty cycles. Collectively, the trucks drove over 23,000 miles during their respective demonstration phases. The ZECT II project was the first of its kind to demonstrate the commercial viability that supported the additional technology breakthroughs for Class 8 zero emission trucks and validations as well as the regulatory basis for all the zero-emission regulation that we know today, such as the Innovative Clean Transit regulation, Advanced Clean Trucks and Clean Fleet regulations.

08 HYDROGEN↗
DOE OSTI2025

Infrared spectral signatures of interfacial water at TiO 2 –electrolyte interfaces from deep potential molecular dynamics

Vibrational spectroscopy is a powerful tool for probing water at oxide–electrolyte interfaces, but its molecular interpretation can be challenging. Here, we employ deep potential long-range molecular dynamics simulations with layer-resolved spectral analysis to investigate the microscopic origins of the infrared (IR) response of water at the interface with anatase TiO 2 (101), a prototypical oxide surface. The calculated interfacial spectra exhibit characteristic modifications compared to bulk water IR spectra, including enhanced intensities, a red shifted and broadened stretching band, and a higher-frequency shoulder, in qualitative agreement with experiments. Spectral decomposition shows that these signatures originate mainly from the first interfacial water layer, dominated by surface-bound H 2 O at Ti 5C sites, with secondary contributions from the second layer. A moderate salt concentration (0.4 M NaCl) leaves both the interfacial structure and the spectra essentially unchanged, while tuning the pH strongly modulates the spectral intensity. We establish a scaling relation linking the spectral intensity to the surface water dissociation fraction and the dipole moment, both governed by interfacial electric fields. These findings provide a microscopic framework for interpreting IR spectra of oxide–electrolyte interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Enabling Stable and Salt-Free Formic Acid Production via Reactive Interface Optimization in Forward-Bias Bipolar-Membrane CO2 Electrolyzers

Electrochemical conversion of CO2 to liquid products is limited by parasitic reactions that consume products and destabilize operation. Here, we show that salt-free formic acid synthesis in a forward-bias bipolar-membrane CO2 electrolyzer is governed by a coupled reaction-transport instability driven by parasitic anode formic acid oxidation. Operando mass spectrometry reveals that this process proceeds through CO-mediated poisoning, identifying catalyst tolerance to CO as a key descriptor of anode selectivity. Among the catalysts examined, PtRu/C preferentially promotes hydrogen oxidation over formic acid oxidation. Coupling this catalyst with transport-interface engineering improves product removal, enhances Faradaic and energy efficiency, and enables stable operation at 200 mA/cm2 for 190 h with a voltage decay of 0.64 mV/h. Techno-economic analysis indicates an 18% reduction in minimum selling price and highlights product concentration as the dominant cost lever. These results establish a general framework for suppressing product oxidation in liquid-product electrolyzers.

Hu, Leiming↗
DOE OSTI2025

Dayflow-PR: High-Resolution Streamflow Reanalysis for Puerto Rico, Version 1.0

This dataset presents a high-resolution historical streamflow reanalysis for NHDPlusV2 stream reaches across Puerto Rico (PR) spanning 1950 - 2019. The reanalysis is generated using the calibrated VIC-RAPID hydrologic modeling framework at the Hydrologic Unit Code Sub-basin (HUC08) scale, forced with sub-daily and daily meteorological forcings from Daymet. Runoff is simulated on 1- and 6-km grids, and the resulting total runoff is routed through the NHDPlusV2 river network using the RAPID routing model to produce Naturalized Streamflow Reanalysis. Where complete observational records are available over 1980 - 2019, streamflows are assimilated (substituted) and subsequently routed downstream through the river network to produce Assimilated Streamflow Reanalysis. The dataset includes streamflow outputs from eight distinct hydrologic modeling configurations along with key performanc evaluation metrics at daily and monthly scales, supporting a wide range of water resource applications. This dataset is derived to support the Non-Powered Dam Assessment, as well as 9505 Secure Water Assessment projects for the US Department of Energy (DOE) Water Power Technologies Office (WPTO). For further details, refer to Ghimire et al. (2023), Kao et al. (2024), and Ghimire et al. (2025).

13 HYDRO ENERGY↗
DOE OSTI2025

Adaptive Dynamic Digital Twin for Test Scenario Generation

Vehicle testing has been an important part in the development of both highly automated vehicles (HAV) and advanced driving assistant systems (ADAS). Obtaining a good representation of the Vehicle Under Test (VUT) is crucial for test scenario library generation (TSLG). Current vehicle testing methods often involve calibrating car-following models using vehicle trajectory data to create static representations that cannot be dynamically updated. For instance, when multiple vehicle trajectories are collected, it is difficult to automatically determine whether a new trajectory improves the model's representativeness or degrades its accuracy. In this paper, we introduce a dynamically updated digital twin modeling framework featuring an adaptive mechanism that evaluates new trajectory data. This mechanism can decide whether to incorporate newly collected data into the current model or create a separate digital twin model when the trajectory significantly differs from prior data. Vehicle location, speed, and acceleration extracted from the newly collected trajectory data are used to support the dynamic update decision. By integrating this digital twin model into the test library generation process, we demonstrate its ability to assist in generating test libraries while effectively handling newly collected data.

Chen, Hanlin [ORNL] (ORCID:0000000165087715)↗
DOE OSTI2024

Increasing the Reproducibility and Replicability of Supervised AI/ML in the Earth Systems Science by Leveraging Social Science Methods

Artificial intelligence (AI) and machine learning (ML) pose a challenge for achieving science that is both reproducible and replicable. The challenge is compounded in supervised models that depend on manually labeled training data, as they introduce additional decision-making and processes that require thorough documentation and reporting. We address these limitations by providing an approach to hand labeling training data for supervised ML that integrates quantitative content analysis (QCA)—a method from social science research. The QCA approach provides a rigorous and well-documented hand labeling procedure to improve the replicability and reproducibility of supervised ML applications in Earth systems science (ESS), as well as the ability to evaluate them. Specifically, the approach requires (a) the articulation and documentation of the exact decision-making process used for assigning hand labels in a “codebook” and (b) an empirical evaluation of the reliability” of the hand labelers. In this paper, we outline the contributions of QCA to the field, along with an overview of the general approach. We then provide a case study to further demonstrate how this framework has and can be applied when developing supervised ML models for applications in ESS. With this approach, we provide an actionable path forward for addressing ethical considerations and goals outlined by recent AGU work on ML ethics in ESS.

58 GEOSCIENCES↗
DOE OSTI2026

Cost of convenience in long-dwell public electric vehicle charging

This paper presents a comprehensive methodology for quantifying trade offs between the cost of charging at public Level-2 charging stations and the inconvenience of using those stations. The paper also includes a methodology for generating synthetic travel itineraries of tens of thousands of drivers and for sizing and placing charging infrastructure to support those itineraries. Inconvenience is quantified by a weighted sum of the time a driver spends traveling between their intended destination and the charging station; weights are derived from the activity interrupted by the driver’s need to move their car. We demonstrate a trade off between cost of charging and inconvenience by varying how far away from their destination drivers are willing to charge. Our results demonstrate the importance of access to stations and suggest that other methods for increasing access, such as increasing the spatial density of stations, could significantly impact charging cost and inconvenience. Moreover, average energy cost may be reduced by introducing managed charging, which also affects inconvenience. The framework presented here can be used to evaluate the overlapping effects of both access and charge management. Furthermore, the framework can be easily extended to include additional factors such as capital costs, enabling thorough evaluation and planning of regional Level-2 charging networks.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗
DOE OSTI2024

RectifHyd Version 2.0: Historical and counterfactual-climatological hydropower monthly generation totals for CONUS plants, 1980 – 2019

This dataset will contain the following files: - RectifHydV2.zip – the RectifHydV2 dataset, split into two files: o RectifHydV2_Actual_MWh.csv: Estimated actual monthly net generation from 590 Hydropower Plants (>10MW nameplate) in CONUS, 1980 – 2019 o RectifHydV2_Counterfactual_MWh.csv: Counterfactual (climate-only) monthly net generation from 590 Hydropower Plants (>10MW nameplate) in CONUS, 1980 – 2019 - RectifHydV2_code.zip: Full data processing pipeline, coded using R {targets} framework. This is a snapshot release (v1.0) of the code repository stored at https://code.ornl.gov/turnersw/rectifhydv2 - RectifHydV2_inputs.zip: Complete set of input data used to create RectifHydV2, organized for direct entry into “/data/” directory of the RectifHydV2 reproducible data pipeline - RectifHydV2_misc.zip: - RectifHydV2_dailyRelease.csv

13 HYDRO ENERGY↗
DOE OSTI2024

An Analysis of the Spatial Variations in the Relationship Between Built Environment and Severe Crashes

Traffic crashes significantly contribute to global fatalities, particularly in urban areas, highlighting the need to evaluate the relationship between urban environments and traffic safety. This study extends former spatial modeling frameworks by drawing paths between global models, including spatial lag (SLM), and spatial error (SEM), and local models, including geographically weighted regression (GWR), multi-scale geographically weighted regression (MGWR), and multi-scale geographically weighted regression with spatially lagged dependent variable (MGWRL). Utilizing the proposed framework, this study analyzes severe traffic crashes in relation to urban built environments using various spatial regression models within Leon County, Florida. According to the results, SLM outperforms OLS, SEM, and GWR models. Local models with lagged dependent variables outperform both the global and generic versions of the local models in all performance measures, whereas MGWR and MGWRL outperform GWR and GWRL. Local models performed better than global models, showing spatial non-stationarity; so, the relationship between the dependent and independent variables varies over space. The better performance of models with lagged dependent variables signifies that the spatial distribution of severe crashes is correlated. Finally, the better performance of multi-scale local models than classical local models indicates varying influences of independent variables with different bandwidths. According to the MGWRL model, census block groups close to the urban area with higher population, higher education level, and lower car ownership rates have lower crash rates. On the contrary, motor vehicle percentage for commuting is found to have a negative association with severe crash rate, which suggests the locality of the mentioned associations.

Alisan, Onur (ORCID:0000000193113984)↗
DOE OSTI2026

Recent efforts of vapour-phase strategies for EUV resist toward high- and hyper-NA extreme ultraviolet lithography

Extreme ultraviolet lithography (EUVL, λ = 13.5 nm) is critical for sub-1 nm technology nodes but remains constrained by inherent trade-offs among resolution, line-edge roughness (LER), and sensitivity. Stochastic effects originating from photon shot noise, low-energy secondary electron blur, and the random distribution of resist components further limit its advancement toward high numerical-aperture (NA, NA = 0.55) and hyper-NA (NA ≥0.75) EUVL. While the optimization of spin-on chemically amplified resists (CARs) continues, metal-oxide resists (MORs) have emerged as strong candidates for next-generation EUVL by incorporating metals with high EUV absorption coefficients, which enhances both resist sensitivity and etch resistance during pattern transfer. Besides spin-coating, recent advances in vapour-phase techniques, such as vapour-phase infiltration (VPI), chemical vapour deposition (CVD), and molecular atomic layer deposition (MALD), offer promising pathways to achieve new resist platforms, such as dry resists, that satisfy the stringent thickness and uniformity requirements of next-generation EUVL. These methods enable the direct incorporation of metal species into existing resist matrices or the formation of hybrid inorganic–organic resist platforms, thereby improving film uniformity, etch durability, and pattern fidelity while mitigating stochastic defects. This review highlights the latest advancements in vapour-phase-synthesized EUV resists, emphasizing material design, lithographic performance, and the underlying exposure mechanisms. Although still emerging, vapour-phase strategies are paving the way for an all-dry integration framework that could improve EUV patterning workflows and meet the demands of future technology nodes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Reinforcement Learning-Based Oscillation Dampening: Scaling Up Single-Agent Reinforcement Learning Algorithms to a 100-Autonomous-Vehicle Highway Field Operational Test

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. Here, we explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Extending tetrahedral network similarity to carbon: A type-I carbon clathrate stabilized by boron

Clathrates are guest/host framework compounds composed of polyhedral cages, yet despite their prevalence among tetrahedral network formers, clathrates with a carbon host lattice remain unrealized synthetic targets. Here, we report a type-I carbon-based framework—a ubiquitous clathrate structure type found throughout compounds containing tetrahedral building blocks. Following a boron-stabilization scheme based on first-principles predictions in the Ca–B–C system at high pressure, type-I Ca 8 B x C 46−x (x ≈ 9) was synthesized in the archetypal $Pm\bar{3}n$ lattice with stability derived from substitutionally disordered boron atoms on hexagonal ring framework positions. The synthesized clathrate, which is recoverable to ambient conditions, expands topological network similarity across tetrahedral systems and opens possibilities for a broad family of diamond-like, carbon-based compounds with tunable properties based on the wide potential for guest/host-atom substitutions and framework versatility.

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

Hydropower Capacity Factor Trends & Analytics for the United States

This data repository contains all code, input data, and data generated for Turner et al. (2024)—“Hydropower capacity factors trending down in the United States”. File descriptions: – hydro-cf-trends-inputs.zip: Full set of input data used in this study, organized for direct entry into “/data” directory of hydro-cf-trends data processing pipeline. – hydro-cf-trends.zip: Full data processing pipeline, coded using the R {targets} framework. This is a snapshot release (v1.0) of the code repository stored at https://code.ornl.gov/turnersw/hydro-cf-trends/. – hydro-cf-trends-results.zip: Provides all dam level results required to reproduce results and graphics in Turner et al. (2024). Dams are identified by the “complxID” (root of the hydropower plant ID in the Existing Hydropower Assets Database, inherited from HILARRI). Results include: • dam_CF_trends.csv: Table of long-term trends in annualized capacity factors for 610 dams and modeled annualized capacity factors for 362 modeled dams (naturalized and assimilated flows). • dam_annualized_CF_gen.csv: Annualized time series of the following variables for each of 610 hydropower dams with nameplate > 5MW – Reported nameplate capacity (MW) – Implied maximum annual generation (MWh) – Reported net generation (MWh) – Computed annual capacity factor – Modeled annual capacity factor (362 modeled plants only)

13 HYDRO ENERGY↗
DOE OSTI2025

Surviving nanoscale interfacial stability in extreme thermal expansion contrast Zn(CN) 2 -epoxy resin matrix composites

Here, we report the remarkable stability at the nanoscale matrix-filler interface in a series of overall low coefficient of thermal expansion (CTE) zinc cyanide (ZC)/epoxy resin composites. These interfaces demonstrate the stability of highly contrasting materials. These composites are designed to optimize the properties of both materials: epoxy resins are valued for their high strength, superb chemical resistance, low dielectric properties, and adhesive abilities. ZC, a model flexible framework, exhibits negative thermal expansion (NTE) behavior and compensates for the epoxy resin’s detrimentally large thermal expansion values. Filled resins minimize the native 65 ppm/°C CTE values to 19 ppm/° C over a wide temperature range while maintaining linearity, yielding composites compatible with typical metal and ceramic substrates’—commonly bonded to the resin— 0–20 ppm/° C CTE values. Additionally, with significant intrinsic differences in the materials, we use wide-angle X-ray diffraction and atomic force microscopy to elucidate thermal movement. The ZC/epoxy interface is surprisingly resilient over 1,000 cycles between -55° C and 75° C, extremes typical to aerospace applications. Further, we show that the resin viscosity remains less than 21 Pa*s at up to 30 vol% ZC, an important consideration for workability. We also discuss settling distribution, glass transition temperature, flexural strength, and longevity. All results point favorably towards practical implementation in low thermal expansion application needs: filling the gap in component design.

42 ENGINEERING↗
DOE OSTI2026

Reservoir Sediment Management and Monitoring Database

Overview This dataset compiles dam sediment management and monitoring information from surveys, case studies, and journal articles. Additionally, features described by the National Inventory of Dams (i.e., presence of sluice gates) are included to indicate known infrastructure features that may address sediment releases. The location and description of records from downstream monitoring gages are catalogued in order to help with tracking conditions over time (e.g., before and after management actions, as operations change, etc.). The data help address national scale understanding of challenges and solutions related to the accumulation of sediment behind a dam as well as downstream passage. Sediment trapping causes problems as it reduces storage capacity, disrupts dam and reservoir function, impedes access for recreation, alters water quality/habitat conditions, and contributes to riverbank and coastal erosion within the reservoir. Data compilation from a variety of sources is a first step towards assessing system-wide efficacy of management solutions. This dataset was developed under the Water Power Technologies Office funded effort which began as a Seedling on Reservoir Sedimentation Data, and was supported by the Reservoir Sedimentation Modeling Framework and Data Analysis project. These projects have addressed challenges in describing sediment transport, trapping, and management at dams throughout the US. Methodology An outer join on dams/reservoirs with surveys and survey reports (documented in the RESSED database, USBR or USACE databases, project websites, etc.) with the National Inventory of Dams, based on the NIDID to determine dams with documented management and/or sluice gates. Additional dams with documented management activity were identified through review of technical articles from the past 25 years in Journal of Hydrology, Journal of Water Resources Planning and Management, Geomorphology, Journal of Hydraulic Engineering, Water, Journal of Cleaner Production, International Journal of Sediment Research, Nature Scientific Reports, Earth Surface Processes and Landforms, and Environmental Science and Pollution Research. Individual records were created for each survey or management activity documented. To evaluate downstream sediment monitoring records, the nhdPlusTools and dataRetrieval packages in R were used to find gages within 10km of each dam in the management database. Length of record and location of matched gages were retrieved for those parameters relevant to sediment concentration or total sediment discharge.

Hansen, Carly [ORNL] (ORCID:0000000193280838)↗