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128 results for “Water flow”
SBC LTER: Ocean: HFR-derived surface flow metrics, surface water retention times, and related factors in the Santa Barbara Channel (2012-2019)
This data package include three files: 1. daily maps of High-Frequency Radar (HFR) measured surface currents, indices of mesoscale eddy locations, and local retention times on a 2km grid; 2. monthly time series of wind stress, alongshore pressure gradient, surface current EOF principal components, vorticity, eddy area, eddy presence, and spatially averaged retention times from January 2012 to December 2019; 3. A MATLAB script for plotting the maps and timeseries. These data were processed in order to investigate the drivers of surface water retention in the Santa Barbara Channel, CA, details of which are available in the study: Brokaw, R.J., D.A. Siegel, and L. Washburn. Physical Drivers of Surface Water Retention in the Santa Barbara Channel. [In preparation for Journal of Geophysical Research: Oceans.]
Discrete water temperature, flow, solar radiation, chlorophyll-a and inundation, Sacramento-San Joaquin Delta, CA, 1999-2019
The objective of our study is to better understand the factors affecting chlorophyll-a production within a floodplain and its transport downstream to determine how lateral connectivity influences longitudinal connectivity. The Yolo Bypass is an engineered floodplain of the Sacramento River that inundates during periods of high outflow via overtopping weirs. Water traveling through the Yolo Bypass flows parallel to the Sacramento River and re-connects to the mainstem at the southern extent of the floodplain. Several monitoring programs in the Sacramento San-Joaquin Delta and Yolo Bypass collect discrete and continuous water quality data, including chlorophyll measurements. For this study, we synthesized available flow, water temperature, chlorophyll and inundation data between March 1999 to December 2019 and modeled the effects of environmental variables and inundation on chlorophyll-a production in the floodplain, the mainstem, and downstream of the floodplain/mainstem.
Great Bay Estuary, NH/ME, Box Model Water Chemistry, Flow, Precipitation, and Seagrass Coverage Data, 2008 - 2023.
This data repository contains compiled surface water (tributary and estuarine), wet deposition, and wastewater effluent chemistry, along with discharge, precipitation totals, and monthly effluent flows necessary for the completion of solute budgets for Great Bay, a subregion of Great Bay Estuary, NH/ME, USA. These datasets are part of on-going monitoring programs in the Great Bay Estuary and Lamprey River Hydrological Observatory. A subset of the monitoring data for the 2008 to 2023 period was compiled. The tributary and estuarine monitoring data were requested from the NH Department of Environmental Services Environmental Monitoring Database as part of the Tidal Tributary and Estuary Water Quality Monitoring Programs. The wet deposition chemistry record is maintained as part of the Lamprey River Hydrologic Observatory. Wastewater effluent chemistry was downloaded from the EPA's Enforcement and Compliance History Online Database. The annual (1996 - 2023) seagrass coverage dataset for Great Bay Estuary reflects coverage of Zostera marina seagrass only and was compiled from annual monitoring reports. Mean daily instantaneous discharge data for the three tidal tributaries used in the load calculations are available from the USGS National Water Information System. Hourly precipitation volume data for the Durham, NH SSW station are available from the NCDC U.S. Climate Reference Network, with minor hourly gaps filled using the University of New Hampshire Durham weather station (https://www.weather.unh.edu).
Abundance, biovolume, and biomass of Synechococcus, eukaryote pico- and nano- phytoplankton, and heterotrophic bacteria from flow cytometry for water column bottle samples on NES-LTER Transect cruises, ongoing since 2018
These data represent the abundance, biovolume, and biomass of prokaryotic phytoplankton, eukaryotic pico- and nano- phytoplankton, and heterotrophic bacteria from discrete flow cytometry samples collected during the Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2018. Samples were collected and preserved from the water column at multiple depths using Niskin bottles on a CTD rosette system along the NES-LTER transect, and analyzed post cruise. Cells were identified and enumerated from the flow cytometry data files based on their scattering, SYBR (525 nm), phycoerythrin (575 nm) and chlorophyll (680 nm) fluorescence signals. Gating was completed manually in the Attune NXT software interface.
2021-2022 West False River Emergency Drought Barrier water quality, flow, and fish monitoring
To manage the critically low 2021 water supply for beneficial uses, DWR installed the temporary emergency drought barrier (EDB) on West False River in the Sacramento–San Joaquin Delta (Delta), approximately 5 miles south of Rio Vista, California, in Contra Costa County in June 2021. To monitor the effectiveness and impacts of the EBD, a monitoring program was initiated to track changes in hydrodynamics, water quality, fish, harmful algal blooms, and aquatic weeds in the vicinity of the EDB. The EDB was left in place during the winter of 2021-2022 and removed in fall of 2022. This data set includes all data collected as part of that monitoring program and subsets of ongoing monitoring programs that were used in the final effectiveness report for the EDB.
Water flow velocity data, Shark River Slough (SRS) near Black Hammock island, Everglades National Park (FCE LTER), South Florida from October 2003 to August 2005
Water velocity data measured every 5 or 15 minutes in Shark River Slough beside Black Hammock tree island, Everglades National Park using Sontek Agronaut water flow sampler.
Water flow velocity data, Shark River Slough (SRS) near Chekika tree island, Everglades National Park (FCE LTER) from January 2006 to March 2021
Water velocity data measured every 5 or 15 minutes in Shark River Slough beside Chekika tree island, Everglades National Park, using Sontek Agronaut water flow sampler. Data collection is complete.
Water flow velocity data, Shark River Slough (SRS) near Frog City, south of US 41, Everglades National Park (FCE LTER) from October 2006 to July 2009
Water velocity data measured every 5 or 15 minutes in Shark River Slough near Frog City jetty, Everglades National Park, using Sontek Agronaut water flow sampler.
Water flow velocity data, Shark River Slough (SRS) near Gumbo Limbo Island, Everglades National Park (FCE) from October 2003 - December 2018
Water velocity data measured every 5 or 15 minutes in Shark River Slough near Gumbo Limbo Island, Everglades National Park, using Sontek Agronaut water flow sampler. Data collection is complete.
Water flow velocity data, Shark River Slough (SRS) near Satinleaf Island, Everglades National Park (FCE LTER) from July 2003 to December 2005
Water velocity data measured every 5 or 15 minutes in Shark River Slough near Satinleaf tree island, Everglades National Park, using Sontek Agronaut water flow sampler.
3-hourly water level records (selected high flow events) for the River Garry at Invergarry (Inverness-shire), Scotland
<p>3-hourly records of stage (water level) for the River Garry at Invergarry (Inverness-shire), Gauge A2, for selected high-flow events 1936-1940. Extracts from a record spanning the period 1936-10-01 to 1944-09-30.</p> <p>Data collected by Capt. W. N. McClean via his organisation River Flow Records and with the assistance of local observers.</p> <p>We acknowledge the sponsorship of Scottish Hydro-Electric and the Scottish Environment Protection Agency in suporting the costs of creating digital time series.</p> <p>Subsequent to the colletion of these records, the River Garry was developed by the construction of dams and hydro power stations below Loch Quoich and Loch Garry.</p> <p>The Scottish Environment Protection Agency (SEPA) subsequently opened a river flow gauging station on the River Garry at Craigard in 1997, approximately 3 km upstream of McClean's gauge, operated until 2011.</p>
Molecular simulations of nanoscale two-phase Couette flow of a water-hexane system on a hydrophobic substrate
<p>This dataset contains the output of Molecular Dynamics simulations (MD) of two-phase Couette flow of water/hexane biphasic systems, in terms of density, velocity and temperature fields. Instructions on how to read and analyze the output files in the <code>.tar.gz</code> archives can be found in these previously-published datasets: <a href="https://doi.org/10.5281/zenodo.8077915">https://doi.org/10.5281/zenodo.8077915</a>, <a href="https://doi.org/10.5281/zenodo.6541983">https://doi.org/10.5281/zenodo.6541983</a></p> <p>The run output files are labeled using the following pattern: <code>hex-ca<capillary-number>-q<partial-charge>.tar.gz</code>. It is possible to obtain the wall speed/contact line speed from the capillary number using the following formula: <code>u_w = U_0*<capillary-number></code>, with <code>U_0 = 37.246 m/s</code>.</p> <p>To reproduce the runs it is necessary to use a specific version of Gromacs that allows for a special algorithm of pressure scaling with position restraints. The code can be obtained by cloning <a href="https://github.com/MicPellegrino/gromacs-flow-field.git">https://github.com/MicPellegrino/gromacs-flow-field.git</a>, and switching to the <code>flow-field-grid-visco-coms-deform</code> branch.</p> <p>The folder <code>conf-wat-hex.zip</code> contains the configuration files to reproduce MD simulations. To prepare the equilibration runs at constant pressure, run after having installed Gromacs:</p> <p><code>gmx grompp -f npt.mdp -p topology.top -c before-npt.gro -r before-npt.gro -o system-npt.tpr</code></p> <p>while to prepare the shear runs:</p> <p><code>gmx grompp -f shear.mdp -p topology.top -c after-npt.gro -r lambda0.gro -rb lambda1.gro -o system-shear.tpr</code></p> <p>Simulations are launched by running:</p> <p><code>gmx mdrun -v -s <tpr-file-name>.tpr <possibly-other-mdrun-flags></code></p> <p>Have fun simulating!</p>
Molecular simulations of nanoscale two-phase Couette flow of a water-hexane system on a hydrophilic substrate
<p>This dataset contains the output of Molecular Dynamics simulations (MD) of two-phase Couette flow of water/hexane biphasic systems, in terms of density, velocity and temperature fields. Instructions on how to read and analyze the output files in the <code>.tar.gz</code> archives can be found in these previously-published datasets: <a href="https://doi.org/10.5281/zenodo.8077915">https://doi.org/10.5281/zenodo.8077915</a>, <a href="https://doi.org/10.5281/zenodo.6541983">https://doi.org/10.5281/zenodo.6541983</a></p> <p>The run output files are labeled using the following pattern: <code>hex-ca<capillary-number>-q<partial-charge>.tar.gz</code>. It is possible to obtain the wall speed/contact line speed from the capillary number using the following formula: <code>u_w = U_0*<capillary-number></code>, with <code>U_0 = 37.246 m/s</code>.</p> <p>To reproduce the runs it is necessary to use a specific version of Gromacs that allows for a special algorithm of pressure scaling with position restraints. The code can be obtained by cloning <a href="https://github.com/MicPellegrino/gromacs-flow-field.git">https://github.com/MicPellegrino/gromacs-flow-field.git</a>, and switching to the <code>flow-field-grid-visco-coms-deform</code> branch.</p> <p>The folder <code>conf-wat-hex.zip</code> contains the configuration files to reproduce MD simulations. To prepare the equilibration runs at constant pressure, run after having installed Gromacs:</p> <p><code>gmx grompp -f npt.mdp -p topology.top -c before-npt.gro -r before-npt.gro -o system-npt.tpr</code></p> <p>while to prepare the shear runs:</p> <p><code>gmx grompp -f shear.mdp -p topology.top -c after-npt.gro -r lambda0.gro -rb lambda1.gro -o system-shear.tpr</code></p> <p>Simulations are launched by running:</p> <p><code>gmx mdrun -v -s <tpr-file-name>.tpr <possibly-other-mdrun-flags></code></p> <p>Have fun simulating!</p>
Experimental data for validation of a variational RANS level III flow model: water waves over an array of obstacles and Ogee weir flows
<p>Experimental dataset for the validation of a variational RANS level III flow model. The experimental data correspond to experiments on unsteady of water waves over an array of obstacles and steady curved flows over an Ogee weir. The experiments were conducted at the Hydraulics Laboratory at the Univeristy of Córdoba. </p>
Water Level, Water Temperature, and Flow Measurements from the Ball Creek weir house #9, Coweeta Hydrologic Laboratory, Otto, NC.
This data set contains water level, water temperature, and calculated discharge values from the Ball Creek weir house #9, Coweeta Hydrologic Laboratory, Otto, NC. Using a pressure transducer, measurements are taken every 60 seconds with the average, minimum, and maximum values for water pressure and water temperature saved to the output data table hourly. Water level and discharge are calculated using the hourly average water pressure, and saved to the online data files.
Microplankton counts from discrete water column samples using flow imaging microscopy (FlowCam) from Lakes Fryxell and Hoare, McMurdo Dry Valleys, Antarctica (2007-2011)
This data package consists of microplankton counts from discrete water column samples collected at various depths in Lake Fryxell and Lake Hoare in the McMurdo Dry Valleys region of Antarctica. Samples were collected and preserved during the austral summer-autumn transition in 2007-2008 and in addition to routine McMurdo Dry Valley Long Term Ecological Research (LTER) core limnological sampling in November and December of 2008, 2010, and 2011. Data were imaged using flow cytometry (FlowCam VS-IV) and classified with statistical image-based software (Visual Spreadsheet, v4.17.14). These data include haptorian ciliates, filamentous cyanobacteria, and coccoidal algae particle counts per milliliter that were automatically classified from user-built libraries and statistical filters based on the morphological characterizations of the plankton.
Haptorian ciliate measurements from discrete water column samples using flow imaging microscopy (FlowCam) from Lakes Fryxell and Hoare, McMurdo Dry Valleys, Antarctica (2007-2020)
This data package consists of particle diameter and biovolume data for haptorian ciliates classified from discrete water column samples collected at various depths in Lake Fryxell and Lake Hoare in the McMurdo Dry Valleys region of Antarctica. Samples were collected and preserved between November 2007 and January 2020 in Lake Fryxell and between November 2007 and March 2008 in Lake Hoare. Samples were collected and analyzed as part of the McMurdo Dry Valleys Long Term Ecological Research (LTER) core limnological sampling. Data were imaged using flow cytometry (FlowCam VS-IV) and imaged particles were classified with statistical image-based software (Visual Spreadsheet, v4.17.14). Diameter and biovolume was generated for each particle using FlowCam’s area-based diameter (ABD) algorithm.
DATA of "Resolving the 2D temporal evolution of subglacial water flow with dense seismic array observations."
<p>The data set contains all data presented in the paper: <strong>Observing the subglacial hydrology network and its dynamics with a dense seismic array</strong> published in PNAS ( <a href="https://doi.org/10.1073/pnas.2023757118">https://doi.org/10.1073/pnas.2023757118</a> )</p> <p>See our online presentation of this dataset: https://meetingorganizer.copernicus.org/EGU2020/EGU2020-10710.html.</p> <p>The present data and code concerns the source location obtained with matched-field-processing analysis and the hydraulic potential calculation (Shreve, R. L. Movement of Water in Glaciers. <em>J. Glaciol.</em> <strong>11</strong>, 205–214 (1972)).</p> <p>We perform source location over 1-sec long signal segment of the vertical component only. We filter the signal within the [3-7] Hz frequency range and coherently apply the MFP each 0.1 Hz within this range. To maximize our algorithm efficiency and minimize computational costs we use a gradient-based minimization algorithm (Nelder-Mead optimization) to converge to the best match between the trial and the observed phase delays rather than an exhaustive grid-search exploration. The convergence criterion is reached when the variance of values obtained over the last 5 iterations of the optimization is smaller than 1e<sup>-2</sup> with a maximum of 3000 iterations. Our 29 different starting points used for optimization are located 250 m below the glacier surface and they uniformly cover an area of 800 x 800 m<sup>2</sup> centered on the array. We set the initial velocity to 1800 m.sec <sup>-1</sup>. The 29 punctual locations found per signal segment (1 sec) after convergence are located all in the same place if a clear global convergence exists (i.e. high MFP output) or at up to 29 different locations if up to 29 local minima exist (i.e. low MFP output).</p> <p>Timeseries of physical quantities can be found here <a href="https://doi.org/10.5281/zenodo.3701520">https://doi.org/10.5281/zenodo.3701520</a></p> <p>Spatial observations acquired during the same period can be found here <a href="https://doi.org/10.5281/zenodo.3971815">https://doi.org/10.5281/zenodo.3971815</a></p> <p> </p> <p>The RESOLVE project has been supported by a grant from LabEx OSUG@2020 (Investissement d’avenir – ANR10LABX56) and by the IDEX Université Grenoble Alpes. Most of the computations presented in this paper were performed using the GRICAD infrastructure (https://gricad.univ-grenoble-alpes.fr), which is supported by Grenoble research communities, and with the CiGri tool (https://github.com/oar-team/cigri) developed by Gricad, Grid5000 (https://www.grid5000.fr) and LIG (<a href="https://www.liglab.fr/">https://www.liglab.fr/</a>).</p> <p> </p> <p>You can find more information on the method and seismic dataset used in this paper here: <a href="https://zenodo.org/deposit/5645545">https://zenodo.org/deposit/5645545</a></p>
Supplementary Information S1 - Detailed results of the CAPRI N-LCA and S2 - Quantification of the main N budget flows in the EU25 agriculture sector of Leip, A., Billen, G., Garnier, J., Grizzetti, B., Lassaletta, L., Reis, S., Simpson, D., Sutton, M. a, de Vries, W., Weiss, F., Westhoek, H. (2015). Impacts of European livestock production: nitrogen, sulphur, phosphorus and greenhouse gas emissions, land-use, water eutrophication and biodiversity. Environ. Res. Lett. 10, 115004. doi:10.1088/1748-9326/10/11/115004
<p>Table S1-1 Quantification of GHG and Nr flow intensities [kg CO2eq (kg product)<sup>-1</sup> yr<sup>-1</sup>] or [g N (kg product)<sup>-1</sup> yr<sup>-1</sup>] with the CAPRI N-LCA model for six main livestock products (BEEF: beef, PORK: pork, EGGS: eggs, POUM: poultry meat; DAIR: milk and dairy products, SGMP: meat from sheep and goats) and six main vegetable food groups (POTA: potatoes, SUGB: sugar beet before processing, OILP: oil seeds before processing; CERR: cereals, LEGU: leguminous crops) as well as other crops (OCRP) and aggregated livestock (ANIMP) and vegetable (CROPP) food. </p> <p>Table S2-1 Quantification of the main N budget flows in the EU25 agriculture sector</p>
Silica dissolution under a flow of pure water at pressure and temperature conditions relevant to geothermal energy extraction
<p>This dataset is a published product of the 'REFLECT' Project - a Horizon Europe project which aims to inform the processes of geothermal energy extraction by determining the effect of relevant fluid properties and reactions in order to enhance predictive geochemical modelling and thus the energy exploitation and life-time of geothermal power plants.</p><p>The dataset records the concentration of silica measured in water that had been passed through a packed column of quartz grains at temperatures from 200 to 450°C and pressures from 150 to 450 bar. Concentrations are reported as g/ml SiO2, measured photometrically. The reader is referred to the full report for deliverable 1.4 of the REFLECT project for details of the experimental set up and interpretation of the data.</p><p>Silica concentrations marked with (a) are believed to be artificially reduced compared to the rest of the dataset due to a reduction in the surface density of active sites during some of the highest dissolution experiments. The final column lists the chronological order in which the measurements were taken to assist with interpretation of this factor.</p><p>The density marked with (b) represents the density of water at 150 bar and 342°C, rather than the measured condition of 148 bar and 344°C. This is to reflect the fact that the solubility measurement suggests the presence of a liquid phase - the conditions chosen represent the closest point on the phase boundary to the measured conditions. The discrepancy may reflect a small shift in the phase envelope due to silica dissolution in addition to any uncertainty in the <i>pT</i> measurements.</p>
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