Zero or not? Causes and consequences of zero-flow stream gage readings
Not provided.
Environmental Sciences & Ecology↗
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Results for “GaGe”
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Materials Data on GaGe(MoS2)4 by Materials Project
GaGe(MoS2)4 crystallizes in the cubic F-43m space group. The structure is three-dimensional. Mo+2.25+ is bonded in a 3-coordinate geometry to six S2- atoms. There are three shorter (2.36 Å) and three longer (3.01 Å) Mo–S bond lengths. Ga3+ is bonded to four equivalent S2- atoms to form GaS4 tetrahedra that share corners with four equivalent GeS4 tetrahedra. All Ga–S bond lengths are 2.34 Å. Ge4+ is bonded to four equivalent S2- atoms to form GeS4 tetrahedra that share corners with four equivalent GaS4 tetrahedra. All Ge–S bond lengths are 2.26 Å. There are two inequivalent S2- sites. In the first S2- site, S2- is bonded in a distorted linear geometry to three equivalent Mo+2.25+, one Ga3+, and one Ge4+ atom. In the second S2- site, S2- is bonded in a 3-coordinate geometry to three equivalent Mo+2.25+ atoms.
36 MATERIALS SCIENCE↗
Materials Data on GaGe by Materials Project
GaGe is Zincblende, Sphalerite structured and crystallizes in the cubic F-43m space group. The structure is three-dimensional. Ga is bonded to four equivalent Ge atoms to form corner-sharing GaGe4 tetrahedra. All Ga–Ge bond lengths are 2.51 Å. Ge is bonded to four equivalent Ga atoms to form corner-sharing GeGa4 tetrahedra.
36 MATERIALS SCIENCE↗
Enhancing Precision and Analysis in Gage Block Calibration with MATLAB
Implementing updated software for the gage block calibration process improved efficiency, data collection, and interpretation, offering updated features tailored to operators.
Mares, Joseph Trinidad↗
Evaluation of XHVRB for Capturing Transition to Detonation as Measured by Embedded Gages.
Abstract not provided.
Tuttle, Leah W.↗
Pan-Arctic daily streamflow at 0.5-degree resolution
Data was derived using daily runoff from models participating in the Coupled Model Intercomparison Project, version 6 (CMIP6) that have been routed through the Model for Scale Adaptive River Transport (MOSART) routing model to represent streamflow at individual streamflow gage locations. Data from 750 streamflow gage locations are represented, which are indexed by gage id according to the metadata.csv file. Streamflow gage location sites were based on gage records downloaded from the United States Geological Survey (USGS), National Water Data (HYDAT) Archive from Canada, and the State Hydrological Institute of Russia. Data are available from 11 Earth System Models (ESMs) in total at a daily timestep with a duration of 1920-2099 (1850-2014 for E3SM only). The spatial domain of the modeled data is 0.5 degree resolution. Earth System Models and Units of mean daily streamflow are presented in cubic meters per second (cms). Data files consist of 11 Earth System Model mean daily streamflow output per gage location in .csv format, 1 metadata file in .csv format and 1 Readme file in .docx format (13 files in total). These data were used to benchmark CMIP6 modeled representations of streamflow against gage records.
54 ENVIRONMENTAL SCIENCES↗
Recent streamflow trends across permafrost basins of North America: Datasets
Climate change impacts, including changing temperatures, precipitation, and vegetation, are widely anticipated to cause major shifts to the permafrost with resulting impacts to hydro-ecosystems across the high latitudes of the globe. However, it is challenging to examine streamflow shifts in these regions owing to a paucity of data, discontinuity of records, and other issues related to data consistency and accuracy. We looked at recent changes in streamflow over 1976-2021 in watersheds affected by varying degrees of permafrost coverage to characterize trends and drivers for a range of watersheds across North America. Data sets are described in detail in the paper associated with this data set, Bennett et al. 2023, Front. Water - Water and Critical Zone, DOI: 10.3389/frwa.2023.1099660.These data contain CSV files of the streamflow, climate, and land surface characteristics for several sites located across the high latitude regions of North America. Both observed and reanalysis data products are provided. These files can be opened using Excel or a text editor, or they can be read, and analyzed in software tools such as Python or R. A brief description of the files is below, and more details can be found in the Methods section.rabpro_stats_north_select_74_55m.csv - This file describes the observed gages used in the analysis.GF31_23_metadat.csv - This file describes the 23 permafrost systems. Columns are as described in rabpro_stats_north_select_74_55m.csv above, with rabpro_id, the id used for the timeseries file mapping in GF31_23_time_series.csv.GF31_23_time_series.csv - This file contains the time series data for the stations described in GF31_23_metadat.csv.GF31_random_reaches_1583.csv - This file describes the 1583 randomly selected permafrost-dominant sites for machine learning analysis.era5_GF31_monthly_vars_random_reaches_1583.csv - This file contains the monthly ERA5 land data for the 1583 randomly selected permafrost-dominant sites.observed.zip: USGS and Hydat station data for the 74 gages analyzed in this study. Monthly, seasonal, and annual streamflow observations for minimum streamflow, mean streamflow, and maximum streamflow. Units are m3/sec. 1975-2022.streamflow_daily_GF31_infilled_1979_2022.csv - infilled daily streamflow data (infilled using GloFAS v 3.1) for 55 gages. Units are m3/sec. 1979-2022.glofas_23.zip - Glofas v3.1 file for the 23 permafrost-dominant gages in the study. Monthly, seasonal, and annual streamflow observations for minimum streamflow, mean streamflow, and maximum streamflow. Units are m3/sec. 1979-2021.glofas_1583.zip - Glofas v3.1 file for the 1583 randomly selected permafrost-dominant gages in the study. Monthly, seasonal, and annual streamflow observations for minimum streamflow, mean streamflow, and maximum streamflow. Units are m3/sec. 1979-2021.
54 ENVIRONMENTAL SCIENCES↗
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)↗
Detection of Critical Surface Features in PTLs and GDLs for Improved Device Performance and Manufacturing Reliability
High points, or features that protrude above the surface of the material, on porous transport layers (PTLs) and gas diffusion layers (GDLs) can be critical features that may affect the manufacturing process and the performance of the device containing the feature. High points on PTLs and GDLs may stress the membrane of a polymer electrolyte membrane (PEM) during lamination and cell operation of a PEM electrolyzer or fuel cell. Additionally, high points on GDLs may impact the reliability of the manufacturing process. Thus, understanding these critical features and developing procedures to detect them are a key part of developing quality control techniques for PTLs and GDLs. This work evaluates the effectiveness of the Keyence VR6200 benchtop-scale structured light optical profilometer for detection of surface protrusions on PTLs and GDLs. Standard testing procedures for detecting and measuring high points were created for use on both material types. These procedures were evaluated using Gage Repeatability and Reproducibility (Gage R&R), where the repeatability, reproducibility, and effectiveness of the system to detect and measure high points were quantified. We have shown with high statistical power that the system is very effective in detection and measurement of high points, with Gage R&R contributions measured to be 2.2% and 3.6% for PTLs and GDLs, respectively.
36 MATERIALS SCIENCE↗
20 Year Daily Average Modeled Velocity and Discharge for Openwater Season at Five Communities on Kuskokwim River, Alaska
This dataset includes modeled velocity and discharge at five communities in the middle Kuskokwim River region: Aniak, Chuathbaluk, Crooked Creek, Red Devil and Stony River. Modeled velocities and discharge represent daily averages calculated for the openwater season (OWS) from June 1 - October 18 over the 20 year period 2000-2019 using the raw data described below and included in this archive; full details of methodology are described in (Brown et al. submitted to Renewable Energy). Raw data inputs to inform the modeling process include in-situ measurements of 1) discharge with an acoustic Doppler current meter (ADCP, 600kHz Workhorse Rio Grande by Teledyne RD Instruments) and a global positioning receiver (GPS, Trimble 5700, 5800 and R8) utilizing Real Time Kinematic (RTK) GPS mode over 1-2 days at each site in 2009 or 2010 (Ravens 2014), and 2) river stage with a water level logger (HOBO U20-001-01 by Onset) over 2-9 weeks at each site (Ravens 2014), 3) in addition to a 20 year long-term discharge record collected at the USGS stream gage site in Crooked Creek (USGS 2016). Raw data (discharge and stage) are included in this archive for two additional communities: Lower Kalskag and Sleetmute, where modeled velocities were not calculated due to equipment failure or loss. The USGS stream gage data at Crooked Creek (USGS 2016) and stream gage methodology (Turnipseed and Sauer 2010) are publicly available online, so the data are not duplicated here.
16 TIDAL AND WAVE POWER↗
Dynamic Tensile Characterization of Thin-Sheet Brittle Metallic Materials
Refractory metals are favorable materials in applications where high strength and ductility are needed at elevated temperatures. In some cases, operating temperatures may be near the melting point of the material. However, as temperature drops, refractory metals typically undergo a significant mechanical response change - ductile-to-brittle transition. These materials may be subjected to high strain rate loading at an ambient temperature state, such as an impact or crash. Knowledge of the high rate material properties are essential for design as well as simulation of impact events. The high rate stress-strain behavior of brittle metallic materials at ambient temperature is rarely studied because of experimental challenges, particularly when failure is involved. Failure typically occurs within the non-gage section of the material, which invalidates any collected stress-strain information. Here, a method to determine a specimen geometry which will produce failures in the gage section is presented. Pure tungsten in thin-sheet form was used as a trial material to select a specimen geometry for high rate Kolsky tension bar experiments. A finite element simulation was conducted to derive a strain correction for more accurate results. The room temperature stress-strain behavior of pure tungsten at a strain rate of 24 s –1 is presented. The outcome of this experimental technique can be applied to other brittle materials for dynamic tensile characterization.
36 MATERIALS SCIENCE↗
Toward Improved Regional Hydrological Model Performance Using State-Of-The-Science Data-Informed Soil Parameters
Accurate soil moisture and streamflow data are an aspirational need of many hydrologically relevant fields. Model simulated soil moisture and streamflow hold promise but models require validation prior to application. Calibration methods are commonly used to improve model fidelity but misrepresentation of the true dynamics remains a challenge. In this study, we leverage soil parameter estimates from the Soil Survey Geographic (SSURGO) database and the probability mapping of SSURGO (POLARIS) to improve the representation of hydrologic processes in the Weather Research and Forecasting Hydrological modeling system (WRF-Hydro) over a central California domain. Our results show WRF-Hydro soil moisture exhibits increased correlation coefficients ( r ), reduced biases, and increased Kling-Gupta Efficiencies (KGEs) across seven in situ soil moisture observing stations after updating the model's soil parameters according to POLARIS. Compared to four well-established soil moisture data sets including Soil Moisture Active Passive data and three Phase 2 North American Land Data Assimilation System land surface models, our POLARIS-adjusted WRF-Hydro simulations produce the highest mean KGE (0.69) across the seven stations. More importantly, WRF-Hydro streamflow fidelity also increases, especially in the case where the model domain is set up with SSURGO-informed total soil thickness. The magnitude and timing of peak flow events are better captured, r increases across nine United States Geological Survey stream gages, and the mean KGE across seven of the nine gages increases from 0.12 to 0.66. Our pre-calibration parameter estimate approach, which is transferable to other spatially distributed hydrological models, can substantially improve a model's performance, helping reduce calibration efforts and computational costs.
54 ENVIRONMENTAL SCIENCES↗
Improving River Routing Using a Differentiable Muskingum‐Cunge Model and Physics‐Informed Machine Learning
Recently, rainfall-runoff simulations in small headwater basins have been improved by methodological advances such as deep neural networks (NNs) and hybrid physics-NN models—particularly, a genre called differentiable modeling that intermingles NNs with physics to learn relationships between variables. However, hydrologic routing simulations, necessary for simulating floods in stem rivers downstream of large heterogeneous basins, had not yet benefited from these advances and it was unclear if the routing process could be improved via coupled NNs. We present a novel differentiable routing method (δMC-Juniata-hydroDL2) that mimics the classical Muskingum-Cunge routing model over a river network but embeds an NN to infer parameterizations for Manning's roughness (n) and channel geometries from raw reach-scale attributes like catchment areas and sinuosity. The NN was trained solely on downstream hydrographs. Synthetic experiments show that while the channel geometry parameter was unidentifiable, n can be identified with moderate precision. With real-world data, the trained differentiable routing model produced more accurate long-term routing results for both the training gage and untrained inner gages for larger subbasins (>2,000 km2) than either a machine learning model assuming homogeneity, or simply using the sum of runoff from subbasins. The n parameterization trained on short periods gave high performance in other periods, despite significant errors in runoff inputs. The learned n pattern was consistent with literature expectations, demonstrating the framework's potential for knowledge discovery, but the absolute values can vary depending on training periods. The trained n parameterization can be coupled with traditional models to improve national-scale hydrologic flood simulations.
54 ENVIRONMENTAL SCIENCES↗
CAMELSH: A Large-Sample Hourly Hydrometeorological Dataset and Attributes at Watershed-Scale for CONUS
We present CAMELSH (Catchment Attributes and Hourly HydroMeteorology for Large-Sample Studies), the first large-sample hydrometeorological dataset at the hourly scale for the contiguous United States. CAMELSH intergrates hourly meteorological time series, catchment attributes and boundaries from GAGES-II and HydroATLAS for 9,008 catchments across diverse climatic, hydrological, and anthropogenic conditions. In addition, hourly streamflow time series is provided for 3,166 catchments. The dataset spans 45 years (1980–2024) with 11 meteorological variables from the NLDAS-2 forcing dataset, from which we compute nine climate indices related to precipitation, evapotranspiration, seasonality, and snow fraction. Additionally, CAMELSH includes two sets of catchment attributes: 439 from GAGES-II and 195 derived from HydroATLAS. These attributes include factors related to climate, geology, hydrology, river/stream morphology, landscape, nutrient, soil, topography, and anthropogenic influences. Developed in accordance with FAIR (Findability, Accessibility, Interoperability, and Reusability) principles, CAMELSH is the first large-sample dataset at an hourly timescale, supporting machine learning applications for short-term streamflow (flood) prediction and advancing data-driven hydrological research across multiple timescales.
54 ENVIRONMENTAL SCIENCES↗
Design and Evaluation of a Ring Tension Test Grip for Remote Mechanical Testing of Irradiated Tubular Specimens
Here, the ring tension test (RTT) is a mechanical testing method for determining bulk mechanical behavior in the circumferential or hoop direction for tubular materials. The test is especially useful for testing materials with anisotropic mechanical properties, such as zirconium alloys, which are commonly used as nuclear fuel cladding. Anisotropy requires direction-specific testing to determine the hoop strength. Historically, several RTT methods and grips have been used, each method has its strengths and weaknesses, and, in all cases, the measured strength is subject to uncertainty due to variations of the testing geometry and experimental tolerances. Recent analysis has shown that grips with a hemicylindrical mandrel configuration are recommended as the most robust configuration. The two strictest aspects to be controlled are the ability to determine gage region orientation and closely matching the size of the mandrels to the test specimen. This last requirement is particularly challenging when the dimensions of the specimen vary because of environmental effects such as dimensional changes due to irradiation. This paper presents a new RTT grip designed to incorporate this mandrel shape, hold the gage at the desired orientation, be suitable for remote operation in a hot-cell environment, and be adaptable for different sizes or variations in the specimen size. The general description and the unique design features of the test specimen and grips are given in detail. The performance of the grips in mechanical testing, including in a remote hot-cell environment, is also provided.
42 ENGINEERING↗
In-situ measurements of chemically and radiatively important atmospheric gases from the Advanced Global Atmospheric Gas Experiment (AGAGE) and affiliated stations.
In the ALE/GAGE/AGAGE global network program, continuous high frequency gas chromatographic measurements of four biogenic/anthropogenic gases (methane, CH4; nitrous oxide, N2O; hydrogen, H2; and carbon monoxide, CO) and several anthropogenic gases that contribute to stratospheric ozone destruction and/or to the greenhouse effect have been carried out at five globally distributed sites for several years. The program, which began in 1978, is divided into three parts associated with three changes in instrumentation: the Atmospheric Lifetime Experiment (ALE), which used Hewlett Packard HP5840 gas chromatographs; the Global Atmospheric Gases Experiment (GAGE), which used HP5880 gas chromatographs; and the present Advanced GAGE (AGAGE). AGAGE uses two types of instruments: a gas chromatograph with multiple detectors (GC-MD), and a gas chromatograph with mass spectrometric analysis (GC-MS). Beginning in January 2004, an improved cryogenic preconcentration system (Medusa) replaced the absorption-desorption module in the GC-MS systems at Mace Head and Cape Grim; this provided improved capability to measure a broader range of volatile perfluorocarbons with high global warming potentials. The Medusa GC-MS systems were subsequently used at other AGAGE stations (Trinidad Head, Barbados, American Samoa, Zeppelin, Jungfraujoch, and Goan) after the initial setup at Mace Head and Cape Grim. More information may be found at the AGAGE home page: https://agage.mit.edu/instruments.Compared to the previous version (https://data.ess-dive.lbl.gov/view/doi:10.3334/CDIAC/ATG.DB1001), the latest update (Agage_gcmd_gcms_data_2021_04_07_tar.gz) includes 6 months of new data through the end of March 2020. Two new compounds, HCFC-132b, and HCFC-133a, are also included in this version. For a complete list of released compounds and used standard scales, please see “AGAGE_scale_2021_v1.pdf” file. Additional information can also be found on the AGAGE website (https://agage.mit.edu).
54 ENVIRONMENTAL SCIENCES↗
The Advanced Global Atmospheric Gases Experiment (AGAGE) Data
In the ALE/GAGE/AGAGE global network program, continuous high frequency gas chromatographic measurements of four biogenic/anthropogenic gases (methane, CH4; nitrous oxide, N2O; hydrogen, H2; and carbon monoxide, CO) and several anthropogenic gases that contribute to stratospheric ozone destruction and/or to the greenhouse effect have been carried out at five globally distributed sites for several years. The program, which began in 1978, is divided into three parts associated with three changes in instrumentation: the Atmospheric Lifetime Experiment (ALE), which used Hewlett Packard HP5840 gas chromatographs; the Global Atmospheric Gases Experiment (GAGE), which used HP5880 gas chromatographs; and the present Advanced GAGE (AGAGE). AGAGE uses two types of instruments: a gas chromatograph with multiple detectors (GC-MD), and a gas chromatograph with mass spectrometric analysis (GC-MS). Beginning in January 2004, an improved cryogenic preconcentration system (Medusa) replaced the absorption-desorption module in the GC-MS systems at Mace Head and Cape Grim; this provided improved capability to measure a broader range of volatile perfluorocarbons with high global warming potentials. The Medusa GC-MS systems were subsequently used at other AGAGE stations (Trinidad Head, Barbados, American Samoa, Zeppelin, Jungfraujoch, and Goan) after the initial setup at Mace Head and Cape Grim. More information may be found at the AGAGE home page: https://agage.mit.edu/instruments.Compared to the previous version (https://data.ess-dive.lbl.gov/datasets/doi: doi:10.15485/1781803), the latest update (Agage_gcmd_gcms.data.2022_01_03.tar.gz) includes 6 months of new data through the end of September 2020. For a complete list of released compounds and used standard scales, please see “AGAGE_scale_2021_v1.pdf” file. Additional information can also be found on the AGAGE website (https://agage.mit.edu).
54 ENVIRONMENTAL SCIENCES↗
The dataset of in-situ measurements of chemically and radiatively important atmospheric gases from the AGAGE and affiliated stations (2022R1)
In the ALE/GAGE/AGAGE global network program, continuous high frequency gas chromatographic measurements of four biogenic/anthropogenic gases (methane, CH4; nitrous oxide, N2O; hydrogen, H2; and carbon monoxide, CO) and several anthropogenic gases that contribute to stratospheric ozone destruction and/or to the greenhouse effect have been carried out at five globally distributed sites for several years. The program, which began in 1978, is divided into three parts associated with three changes in instrumentation: the Atmospheric Lifetime Experiment (ALE), which used Hewlett Packard HP5840 gas chromatographs; the Global Atmospheric Gases Experiment (GAGE), which used HP5880 gas chromatographs; and the present Advanced GAGE (AGAGE). AGAGE uses two types of instruments: a gas chromatograph with multiple detectors (GC-MD), and a gas chromatograph with mass spectrometric analysis (GC-MS). Beginning in January 2004, an improved cryogenic preconcentration system (Medusa) replaced the absorption-desorption module in the GC-MS systems at Mace Head and Cape Grim; this provided improved capability to measure a broader range of volatile perfluorocarbons with high global warming potentials. The Medusa GC-MS systems were subsequently used at other AGAGE stations (Trinidad Head, Barbados, American Samoa, Zeppelin, Jungfraujoch, and Goan) after the initial setup at Mace Head and Cape Grim. More information may be found at the AGAGE home page: https://agage.mit.edu/instruments. Data from the AGAGE and affiliated stations (total of 9 sites) between August 1993 and March 2021 are provided in “Agage_gcmd_gcms_data_2022_05_26_tar.gz” (compressed tar file). The metadata file has information on each station and currently released species. The standard scales used in archived species are listed in "AGAGE_scale_2022_v1.pdf". Additional information can be found on the AGAGE website (https://agage.mit.edu).
54 ENVIRONMENTAL SCIENCES↗