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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Construction Support for New Slab Creek Powerhouse Project (Final Technical Report)

The Sacramento Municipal Utility District (SMUD) has constructed a new powerhouse and Boating Flow Release Facility (BFRF) ¼ mile downstream of the existing Slab Creek Dam with the assistance of grant funding from the Department of Energy in the amount of $1.5 million. Slab Creek Dam impounds 16,600 acre-feet of storage and has a normal full pool elevation of 1850ft. Water is conveyed from Slab Creek Reservoir through a 4.9 mile power tunnel to the 224 MW White Rock Powerhouse which discharges into Chili Bar Reservoir. A small 450 kW powerhouse located at Slab Creek Dam utilizes the original license in-stream flow requirement. The new license (FERC Project No. 2101-084) requires significantly more instream flows immediately below the dam for aquatic preservation and recreational flows over the original license. The terms of the new license allow the Slab Creek Powerhouse to utilize the original required dam releases, while the new South Fork Powerhouse will use the new instream flow requirements above the original license requirement. The South Fork Powerhouse routes flows back to the South Fork of the American River via a new penstock that is tied into the White Rock Tunnel at Adit #3. This new penstock bifurcates at the Adit #3 portal with one leg going to the BFRF and the other to the new powerhouse. The South Fork Powerhouse is a single generating unit with a capacity of 2.98 kVA. The BFRF is valve house with an energy dissipation chamber for a 60” fixed cone valve capable of passing 1,300 cfs for meeting the recreational flow requirements of the license.

power tunnel↗
DOE OSTI2022

Scalable deep learning for watershed model calibration

Watershed models such as the Soil and Water Assessment Tool (SWAT) consist of high-dimensional physical and empirical parameters. These parameters often need to be estimated/calibrated through inverse modeling to produce reliable predictions on hydrological fluxes and states. Existing parameter estimation methods can be time consuming, inefficient, and computationally expensive for high-dimensional problems. In this paper, we present an accurate and robust method to calibrate the SWAT model (i.e., 20 parameters) using scalable deep learning (DL). We developed inverse models based on convolutional neural networks (CNN) to assimilate observed streamflow data and estimate the SWAT model parameters. Scalable hyperparameter tuning is performed using high-performance computing resources to identify the top 50 optimal neural network architectures. We used ensemble SWAT simulations to train, validate, and test the CNN models. We estimated the parameters of the SWAT model using observed streamflow data and assessed the impact of measurement errors on SWAT model calibration. We tested and validated the proposed scalable DL methodology on the American River Watershed, located in the Pacific Northwest-based Yakima River basin. Our results show that the CNN-based calibration is better than two popular parameter estimation methods (i.e., the generalized likelihood uncertainty estimation [GLUE] and the dynamically dimensioned search [DDS], which is a global optimization algorithm). For the set of parameters that are sensitive to the observations, our proposed method yields narrower ranges than the GLUE method but broader ranges than values produced using the DDS method within the sampling range even under high relative observational errors. The SWAT model calibration performance using the CNNs, GLUE, and DDS methods are compared using R 2 and a set of efficiency metrics, including Nash-Sutcliffe, logarithmic Nash-Sutcliffe, Kling-Gupta, modified Kling-Gupta, and non-parametric Kling-Gupta scores, computed on the observed and simulated watershed responses. The best CNN-based calibrated set has scores of 0.71, 0.75, 0.85, 0.85, 0.86, and 0.91. The best DDS-based calibrated set has scores of 0.62, 0.69, 0.8, 0.77, 0.79, and 0.82. The best GLUE-based calibrated set has scores of 0.56, 0.58, 0.71, 0.7, 0.71, and 0.8. The scores above show that the CNN-based calibration leads to more accurate low and high streamflow predictions than the GLUE and DDS sets. Our research demonstrates that the proposed method has high potential to improve our current practice in calibrating large-scale integrated hydrologic models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Patterns, drivers, and a predictive model of dam removal cost in the United States

Given the burgeoning dam removal movement and the large number of dams approaching obsolescence in the United States, cost estimating data and tools are needed for dam removal prioritization, planning, and execution. We used the list of removed dams compiled by American Rivers to search for publicly available reported costs for dam removal projects. Total cost information could include component costs related to project planning, dam deconstruction, monitoring, and several categories of mitigation activities. We compiled reported costs from 455 unique sources for 668 dams removed in the United States from 1965 to 2020. The dam removals occurred within 571 unique projects involving 1–18 dams. When adjusted for inflation into 2020 USD, cost of these projects totaled $\$1.522$ billion, with per-dam costs ranging from $\$1$ thousand (k) to $\$268.8$ million (M). The median cost for dam removals was $\$157$k, $\$823$k, and $\$6.2$M for dams that were< 5 m, between 5–10 m, and > 10 m in height, respectively. Geographic differences in total costs showed that northern states in general, and the Pacific Northwest in particular, spent the most on dam removal. The Midwest and the Northeast spent proportionally more on removal of dams less than 5 m in height, whereas the Northwest and Southwest spent the most on larger dam removals > 10 m tall. We used stochastic gradient boosting with quantile regression to model dam removal cost against potential predictor variables including dam characteristics (dam height and material), hydrography (average annual discharge and drainage area), project complexity (inferred from construction and sediment management, mitigation, and post-removal cost drivers), and geographic region. Dam height, annual average discharge at the dam site, and project complexity were the predominant drivers of removal cost. The final model had an R 2 of 57% and when applied to a test dataset model predictions had a root mean squared error of $\$5.09$M and a mean absolute error of $\$1.45$M, indicating its potential utility to predict estimated costs of dam removal. We developed a R shiny application for estimating dam removal costs using customized model inputs for exploratory analyses and potential dam removal planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1973

Evaluation of ERTS data for certain hydrological uses

The author has identified the following significant results. Melting ice has been detected in Lake Erie by comparison of visible and near infrared differential reflectance. This melting condition is confirmed by meteorological ground truth data and concurrent NOAA-2 thermal infrared data. Using near-synchronous ERTS-1 data, it was possible to determine the approximate ground resolution of NOAA-2 very high resolution radiometer by comparing the smallest identifiable ice crack in the imagery and measuring the same crack on the ERTS-1 image. It was determined that photointerpretation and analysis of a single Lake Erie image can, under certain conditions, provide meaningful data on ice dynamics. ERTS-1 imagery is effective for icepack monitoring of the Great Lakes, but the sampling interval of 18 days imposes a severe limitation. Maps of the snow cover in the American River basin for 16 March 1973 have been prepared using all four bands.

Wiesnet, D. R.↗
NASA NTRS1973

Evaluation of ERTS data for certain hydrological uses

The author has identified the following significant results. A snow-extent map of the American River basin was prepared for 27 May 1973 from MSS band 4 imagery. The basin was 14% snow covered. NOAA-2 visible band imagery was used to determine date of disappearance of snow in the basin: 15 July 1973. A snowmelt curve comparing ERTS-1 and NOAA-2 snow-extent maps is provided. ERTS-1 data were superior in quality and outstanding in cartographic fidelity and were found to be an excellent control or calibration for the distorted and coarse (1 km) imagery from NOAA-2's VHRR which, however, is available on a daily basis.

Wiesnet, D. R.↗
NASA NTRS1974

Snow-extent mapping and lake ice studies using ERTS-1 MSS together with NOAA-2 VHRR

Five snow extent maps of the 5,601 sq km American River Basin were prepared using a Zoom Transfer Scope from ERTS-1 MSS band 4 imagery. The maps were generally completed within one hour. A snowmelt curve based on ERTS-1 imagery was used as a calibration standard or comparison for maps prepared from NOAA-2 VHRR imagery in the same manner. Cost comparisons with U-2 derived imagery indicate that ERTS-1 snow mapping of the basins is six times faster. Conservative estimates of comparable aircraft snow survey flights yields a cost figure 200 times that of the ERTS-1 snow map. Snow mapping attempts in the Lake Ontario Basin demonstrated that ERTS-1 is not well suited to large basins. Optimum size of basins for ERTS studies is believed to range from about 250 sq km to 30,000 sq km. The value of the ERTS-1 MSS for Great Lake ice evaluation was proved during the past winter on Lake Erie. Not only were ice features and types of ice identified, but melting ice was detected through the combined use of band 5 and band 7. Ice movement (direction and speed) was mapped by examining imagery from two successive days.

Wiesnet, D. R.↗
NASA NTRS1986

Application of Thermal Infrared Multiband Scanner (TIMS) data to mapping of Plutonic and stratified rock and assemblages in accreted terrains of the Northern Sierra, California

The Thermal Infrared Multispectral Scanner (TIMS) data were acquired over the Donner Pass area in California on September 12, 1985. The higher peaks in the area approach 9,200 feet in elevation, while the canyon of the north fork of the American River is only 3000 feet in elevation. The vegetation is dominated by conifers, although manzanita and other shrubs are present in areas where soils have developed. The data contain noise patterns which cut across scan lines diagonally. The TIMS data were analyzed using both photointerpretative and digital processing techniques. Preliminary image interpretation and field analysis confirmed that TIMS image data displays the chert units and silicic volcanics as bright red. The imagery appears to display zoning in the batholithic and hypabyssal intrusive rocks, although this was not field checked at this time. Rocks which appear to be more dioritic in composition appear purple on the imagery, while rocks more granitic in composition appear shades of red and pink. Areas that have more than 40% vegetative cover appear green on the imagery.

Taranik, James V.↗
DOE OSTI2024

Collateral benefits: River flow normalization for endangered fish enabled riparian rejuvenation

Abstract Like most rivers worldwide, the transboundary North American Kootenay/i River has experienced multiple impacts including watershed developments, river channelization, and floodplain clearing, draining, and diking. Construction of Libby Dam was authorized by the 1964 Columbia River Treaty (CRT) between the United States and Canada, and in 1975 began regulating downstream flows for flood risk management and hydropower generation. Following cumulative impacts, the endemic Kootenai River White Sturgeon population collapsed and was designated as endangered in 1994 (U.S. Endangered Species Act). Subsequent Biological Opinions from the U.S. Fish and Wildlife Service prescribed Libby Dam operations to provide springtime flow pulses for sturgeon spawning. These provided the unanticipated benefit of substantial seedling recruitment of native and introduced riparian cottonwoods and willows. The regulated flow regime was further adaptively managed to provide a more normative (natural) regime, to balance ecological functions with flood risk management and hydropower generation. The broadened ecological considerations would be consistent with the proposed priorities for the modernization of the international CRT. The observed responses revealed that (1) diverse aquatic and riparian organisms are dependent on common river flow characteristics; (2) a normalized flow regime provided substantial ecological benefits; and (3) due to multiple influences, hybrid ecosystems develop along regulated rivers, with a blending of natural and altered processes and communities. For other regulated rivers, we recommend that (1) high springtime flows be allowed, as feasible; (2) followed by the gradual post‐peak recession; and (3) the maintenance of sufficient flows through the warm and dry interval of mid to late summer.

Rood, Stewart B.↗
DOE OSTI2026

Data and script associated with “Shifts in Rain-Snow Partitioning Drive Faster Water Transit Times in the US Pacific Northwest”

This data package contains the data and code to use and run the Water Tracer enabled version of the Weather Research and Forecasting Hydrologic model (WT-WRF-Hydro) with the Sequential Precipitation Input Tagging (SPIT) framework. It is associated with the publication “Shifts in Rain-Snow Partitioning Drive Faster Water Transit Times in the US Pacific Northwest” published in Scientific Reports (Butler et al., 2026; https://doi.org/10.1038/s41598-026-46539-1). We use the Continental U.S. (CONUSII; Rasmussen et al., 2021) dataset to force the model with an historical climate (2006–2013) and a future climate (2086–2093) with a representative carbon pathway (RCP) 8.5 scenario. We use the model to calculate water transit times in five headwater catchments within the U.S. Pacific Northwest. We also show key hydrologic and environmental variables that affect water transit times and changes in the future. Finally, we use observed data to validate the model such as stream water isotopes, snowpack characteristics, and stream discharge. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. The data package consists of 11 folders: (1) "Figures" contains the exported figures used in the manuscript; (2) "Model_Isotope_Date" contains the WT-WRF-Hydro isotope date used in model validation; (3) “Model_Outputs_Future” contains the WT-WRF-Hydro future climate outputs; (4) “Model_Outputs_Historical” contains the WT-WRF-Hydro historical climate outputs; (5) “Model_Outputs_Weights_Areas” contains the WT-WRF-Hydro weights per catchment used to calculate water transit times and isotopes in stream water; (6) “MODIS_data_scripts” contains data used to validate snow conditions in the study area; (7) “Observed_Flow_Data” contains the observed streamflow data used in model validation; (8) “Observed_Isotope_Data” contains the observed stream water isotope data used in model validation; (9) “Scripts” contains the Python scripts used to general results and the figures; (10) “Statistic_Outputs” contains the water transit time statistical outputs reported in this manuscript; (11) “Validation_SNOTEL” contains the SNOTEL data used in model validation. The files in this data package have the following file extensions: .tif, .txt, .csv, .pdf, .py, .jpg, and .png.

American River↗
DOE OSTI2020

Detecting Rain–Snow-Transition Elevations in Mountain Basins Using Wireless Sensor Networks

Here, to provide complementary information on the hydrologically important rain–snow-transition elevation in mountain basins, this study provides two estimation methods using ground measurements from basin-scale wireless sensor networks: one based on wet-bulb temperature T wet and the other based on snow-depth measurements of accumulation and ablation. With data from 17 spatially distributed clusters (178 nodes) from two networks, in the American and Feather River basins of California’s Sierra Nevada, we analyzed transition elevation during 76 storm events in 2014–18. A T wet threshold of 0.5°C best matched the transition elevation defined by snow depth. Transition elevations using T wet in upper elevations of the basins generally agreed with atmospheric snow level from radars located at lower elevations, while radar snow level was ~100 m higher due to snow-level lowering on windward mountainsides during orographic lifting. Diurnal patterns of the difference between transition elevation and radar snow level were observed in the American basin, related to diurnal ground-temperature variations. However, these patterns were not found in the Feather basin due to complex terrain and higher uncertainties in transition-elevation estimates. The American basin tends to exhibit 100-m-higher transition elevations than does the Feather basin, consistent with the Feather basin being about 1° latitude farther north. Transition elevation averaged 155 m higher in intense atmospheric river events than in other events; meanwhile, snow-level lowering was enhanced with a 90-m-larger difference between radar snow level and transition elevation. On-the-ground continuous observations from distributed sensor networks can complement radar data and provide important ground truth and spatially resolved information on transition elevations in mountain basins.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Prefabricated Zero Ascend Omnispecies (ZAO) Modular Fish Passage Modules Using Advanced Manufacturing Techniques

The Zero Ascend Omnispecies (ZAO) fish passage attraction module “ZAO Attractor” is a novel system designed to facilitate upstream passage for a broad spectrum of fish species, with a particular focus on American shad and river herring (alewife and/or blueback herring). Combining the use of prefabricated, modular components with advanced manufacturing, the ZAO aims to provide a cost-effective and scalable solution for fish passage attractions across various hydropower sites. The system features a surface level entry, so fish do not need to climb. In addition, it is designed to be adjusted and repositioned to create the most effective attraction flows by managing the outflows from hydropower turbines. Budget Period 1 (BP1) focused on the design and modeling of the ZAO Attractor and demonstrated the engineering feasibility of a modular, prefabricated, hydrodynamically efficient structure with surface level entry and passage. It was discovered that there were limited published studies on the direct correlation between quantified flow patterns and fish attraction, emphasizing the need for controlled studies to observe and measure these effects. In Budget Period 2 (BP2), controlled studies with live fish were prioritized to address these complexities. In conclusion, the ZAO fish passage attraction module presents a promising approach to fish passage at hydropower stations, with the potential to balance environmental concerns with renewable energy development. However, further field validation and optimization are necessary to ensure its effectiveness and practicality in real-world applications.

13 HYDRO ENERGY↗
NASA NTRS1996

MCTP Summer Research Internship Program. Research Presentation Day: Experience Mathematics and Science in the Real World

This paper presents the summaries of the MCTP Summer Research Internship Program. Technological areas discussed include: Mathematical curriculum development for real world problems; Rain effects on air-water gas exchange; multi-ring impact basins on mars; developing an interactive multimedia educational cd-rom on remote sensing; a pilot of an activity for for the globe program; fossils in maryland; developing children's programming for the american horticultural society at river farm; children's learning, educational programs of the national park service; a study of climate and student satisfaction in two summer programs for disadvantaged students interested in careers in mathematics and science; the maryland governor's academy, integrating technology into the classroom; stream sampling with the maryland biological stream survey (MBSS); the imaging system inspection software technology, the preparation and detection of nominal and faulted steel ingots; event-based science, the development of real-world science units; correlation between anxiety and past experiences; environmental education through summer nature camp; enhancing learning opportunities at the Salisbury zoo; plant growth experiment, a module for the middle school classroom; the effects of proxisome proliferators in Japanese medaka embryos; development of a chapter on birth control and contraceptive methodologies as part of an interactive computer-based education module on hiv and aids; excretion of gentamicin in toadfish and goldfish; the renaissance summer program; and Are field trips important to the regional math science center?

Source record↗
DOE OSTI2025

Metagenome-assembled genomes from topsoils along a hillslope water gradient across early snowmelt to late summer in East River, CO

Drought is changing the American Mountain West at unprecedented rates with unknown consequences to soil microbiome composition and function. As a part of LBNL Watershed Science Focus Area (SFA), we investigated shifts in microbial community and transcriptional activity on a subalpine conifer-meadow transition zone throughout the summer of 2023 as soil dried down. This work took place in Crested Butte, CO on Snodgrass mountain, using a proxy for drought conditions.Here we present metagenome assembled genomes (MAGs) for the bacterial and archaeal community at 0-10cm from three sites along a hillslope water gradient across five timepoints from early snowmelt to late summer. 42 metagenomes were sequenced at Joint Genome Institute (JGI) and can be found under the JGI GOLD (Genomes Online Database) sequencing project Gs0166660. Metagenomes were assembled through an inhouse pipeline (see methods), binned using four autobinners (concoct, maxbin2, metabat2, and vamb) and consolidated using dastool. The consolidated bins from all metagenomes were pooled, filtered by completeness (>70%) and contamination (<10%), and dereplicated at 95% ANI using drep. This dataset (1) a zip file of 157 MAGs (as fasta files, Gs0166660_bins_tar.gz), (2) sample metadata file with sample IGSNs (International Generic Sample Numbers) (samples.csv), (3) bounding box coordinates for the sampled locations (Gs0166660.kml), (4) metagenome assembly and coassembly metadata file listing IMG/M (Integrated Microbial Genomes/Metagenomes) metagenome accessions linking samples to metagenomes (EastRiver_Drought_ESSDive_Metadata.csv), (5) location metadata file (locations.csv), (6) file-level metadata file (flmd.csv) and (7) data dictionary (dd.csv) file.This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1982

A satellite magnetic model of northeastern South American aulacogens

Magnetic modeling of the Amazon River and Takatu Aulacogens in northeastern South America illustrate the utility of satellite magnetic data in characterizing the properties and structure of the lithosphere. Specifically, reduction of preliminary Magsat scalar magnetic anomaly data to an equivalent condition of vertical polarization shows a general correlation between magnetic anomaly minima and the Amazon River and Takatu Aulacogens. Surface gravity data demonstrate a correlative positive anomaly. Spherical earth modeling of the magnetic data indicates a less magnetic crust associated with the aulacogens which is compatible with previous studies over the Mississippi River Aulacogen and Rio Grande Rift in North America.

Longacre, M. B.↗
DOE OSTI2022

Radiological Considerations Supporting the American Medical Isotope Producer Niowave

This report provides a summary of work performed by Savannah River National Laboratory (SRNL) during FY22 in support of Niowave, an American Medical Isotope Production (AMIP) facility. SRNL served in a technical support role, funded by NA-231, supporting Niowave in the beginning of non radiological functional testing of their airport facility in FY22. Through this agreement, SRNL provides Niowave access to subject matter experts (SMEs) for questions that may arise during the drafting of engineering plans, facility policies, and/or response procedures. This report summarizes discussions between SRNL and Niowave about guidance concerning issues with the floor of the hot cells, dispersible removable contamination (beta emitting fission product), hot cell operation specifically utilization of cameras or mirrors, and the process for removing contaminated waste from the hot cell. Lessons learned and other various resources provided to Niowave by SRNL during FY22 are referenced in this report. This work was funded through NNSA’s Office of Material Management and Minimization, Conversion Office (NA-231).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Deep Learning for Fish Identification from Sonar Data (CRADA 481 Final Report)

In eastern regions of the United States, the American eel is a species of management and regulatory concern because of significant population declines, despite the species’ previous abundance in all tributaries of rivers flowing into the Atlantic Ocean. The American eel is also a candidate for listing under the U.S. Endangered Species Act. While hydropower construction and operation are only one of several factors contributing to this population decline, such a listing could impose additional regulatory challenges for a large number of hydropower projects. In this CRADA project, we improved technologies for identifying migrating eels with the goal of reducing the cost and time required for future American eel hydropower impact assessment and mitigation studies, while maintaining accuracy. We built on results from a previous FOA project (FOA# DE-FOA-0001662), led by the Electric Power Research Institute (EPRI), which developed a highly accurate, deep-learning method for identifying migrating eels from imaging sonar data. The current study aimed to further optimize this deep-learning model, originally designed for image classification, and to develop an object detection software capable of identifying fish from sonar videos in real time, enabling the detection of events like fish migrations and specific species, such as the American eel, at hydropower dams. The data conversion algorithms were packaged as software with a graphical user interface, and the software is evaluated by external collaborators. We focused on the American eel in this project and explored the transferability of the developed deep learning models to the sea lamprey, given the similar body shape and swimming behavior between the two species.

13 HYDRO ENERGY↗
DOE OSTI2024

The Iowa Tribe of Kansas and Nebraska: Advancing Clean, Resilient, and Sovereign Energy (Summary Report of Communities LEAP Activities)

The Iowa Tribe of Kansas and Nebraska (ITKN) is a federally recognized Native American Tribe located along the Missouri River on the border of northeast Kansas and southeastern Nebraska. There are over 800 residents (Tribal citizens and non-Tribal) who live on the reservation, as well as more than 500 people who visit or work on the reservation on a daily basis. The ITKN faces many energy challenges, including rising service costs and dozens of power outages annually that impact resident well-being and business activities on Tribal lands. Power service issues are made more challenging by the remoteness of the reservation, which is 20 miles from the nearest town. Despite this, the ITKN has a long history of cultural and economic resilience: Local self-reliance, environmental stewardship, respecting the carrying capacity of the land, and strengthening the community are Tribal communities' traditional strengths. Long-term energy goals for the ITKN are centered around achieving energy sovereignty. Priority actions include: (1) Establishing a Tribal Utility Authority (TUA) to promote social welfare and community development.; (2) Deploying renewable community microgrids with ground-mount solar arrays and sustainable energy storage systems to advance energy sovereignty, resilience, and reliability. To advance these goals, the ITKN partnered with the U.S. Department of Energy's (DOE's) Communities LEAP (Local Energy Action Program) pilot. From August 2022 to March 2024, the ITKN community coalition collaborated with technical assistance providers at DOE's National Renewable Energy Laboratory (NREL) and Sandia National Laboratories to evaluate TUA planning needs and microgrid deployment scenarios. This final report details the Communities LEAP technical assistance process, models and analysis performed, and results.

24 POWER TRANSMISSION AND DISTRIBUTION↗