Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
13
datasets available to search
ShareScore release 0.9.0
Dataset results
13 results for “groundwater temperature”
Groundwater levels and temperature in coastal tundra adjacent to Simpson Lagoon, Alaska, 2022
The coastal tundra adjacent to Simpson Lagoon, along Alaska's Beaufort Sea coast, was visited in July and September/October 2022 to assess coastal groundwater dynamics along the lagoon. Groundwater levels were monitored in five piezometers aligned in a transect oriented perpendicular to Simpson Lagoon, as well as surface water levels in the lagoon. Loggers were deployed on July 22, 2022, and collected on September 29, 2022. Data include surface water and groundwater elevation data from July 22, 2022, to September 29, 2022, with the elevation relative to a local datum. All levels have been corrected for barometric pressure (see methods). Also included is groundwater temperature data from the well closest to the lagoon (Well 5).
Continuous groundwater well temperature, salinity and water level measurements at the GCE-LTER Seawater Addition Long-Term Experiment (SALTEx) site from May 2014 to February 2018
The Georgia Coastal Ecosystems LTER Seawater Addition Long-Term Experiment (SALTEx) is a large-scale field experiment designed to simulate saltwater intrusion in a tidal freshwater wetland to predict how chronic (Press) and acute (Pulse) salinization will affect this and other tidal freshwater ecosystems. In order to characterize groundwater salinity, temperature, and plot flooding following experimental manipulation, unvented water pressure, temperature and conductivity were continuously measured in a PVC groundwater well installed at the SALTEx site. Measurements were made at the bottom of the well using a submerged Schlumberger CTD-Diver logger every 15 minutes from 30-May-2014 to 14-Feb-2018. In February 2016 a second CTD-Diver was deployed near the top of the well. Data were downloaded from the loggers using Diver Office communication software, then imported into MATLAB for post-processing, quality control and documentation. Raw, unvented pressure readings were corrected for atmospheric pressure and sensor height from the bottom of the well to generate corrected pressure readings, then water level, salinity and density were calculated from the measured variables using UNESCO algorithms. These data were collected as part of the Georgia Coastal Ecosystems LTER SALTEx project (http://gce-lter.marsci.uga.edu/public/app/send_project_eml.asp?id=73), and will be updated annually.
AGW03 Konza Prairie Long-term high frequency groundwater level and temperature from wells on N04d
The objectives of this project are to quantify the seasonably variable timing among meteoric precipitation, groundwater recharge, and groundwater temperature. Hypotheses are: 1. Because of the karst-like characteristics of the aquifers in N04d (and by extension, the entire region), recharge will be rapid during moderately large precipitation events where fractures are enlarged by dissolution and therefore highly conductive, except during the most active part of the growing season. 2. The recharge efficiency of the aquifers will be spatially variable, with highest hydraulic conductivity (because of solution enlargement of fractures) near the riparian zone. 3. Groundwater temperature will vary continuously over the year and also demonstrate abrupt changes after recharge-effective precipitation events when the precipitation temperature is different from the groundwater temperature. Because the aquifers are merokarst and recharge is rapid, data are recorded at high frequency (5 minute intervals).
Water table elevation and groundwater temperature from the outwash plain of the Otemma glacier forefield (Switzerland) from 2019 to 2021
<p><strong>Water table elevation and groundwater temperature from the outwash plain of the Otemma glacier forefield (Switzerland) from 2019 to 2021.</strong><br> Data were collected by the research teams of Bettina Schaefli<sup>1,2</sup>, Stuart N. Lane<sup>1</sup>.</p> <p><sup>1</sup> Institute of Earth Surface Dynamics (IDYST), University of Lausanne, 1015 Lausanne, Switzerland</p> <p><sup>2</sup> Institute of Geography (GIUB), University of Bern, 3012 Bern, Switzerland</p> <p>For further information, please contact:</p> <ul> <li>tom.muller.1@unil.ch</li> </ul> <p><strong>This dataset is first referenced and discussed in the research paper by Müller et al., 2022.</strong></p> <p>------------------------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p><strong>Data Description</strong></p> <p>9 piezometers consisting of fully screened plastic tubes were installed at an averaged depth of 1.5 to 2m in the outwash plain of the Otemma glacier forefield (WGS84 : 45.93434 / 7.41209). They cover four transects perpendicular to the stream from downstream (A) to upstream to (D).</p> <p>Water table elevation and temperature were recorded in each well at a 10 minute interval using SparkFun MS5803-14BA pressure sensors. Sensor resolution is 1 mm and 0.01 °C, sensor accuracy is ± 2 cm and ± 0.8°C. Sensor bias was verified and corrected by bi-monthly manual groundwater stage measurements. Water temperature was not manually corrected and may be subject to some unidentified bias.</p> <p>Piezometer location can be visualized in<strong><em> overview_piezo.jpg</em> </strong></p> <p>Piezometer coordinates are available in<strong> </strong>shapefile <strong><em>GPS_piezometers.zip</em></strong> (coordinate system: swiss LV95 (EPSG:2056))</p> <p>Piezometers name matches the labelling used in Müller et al. 2022 (A1,A2 to D1,D2). Two additionnal piezometers (BinjUp & BinjDown) used for a specific salt tracing analysis (see <em>ERT_timelapse_salt_tracer.gif </em>at <a href="https://zenodo.org/record/6342767#.YjBRmTXjJlh">https://zenodo.org/record/6342767#.YjBRmTXjJlh</a>) are also available. Finally an additional piezometer (B1-2) located between B1 and B2 is also available although it was not used in Müller et al. 2022.</p> <p><strong>Data Structure</strong></p> <p><strong>df_piezometers.csv</strong> is formated as a tidy dataframe with 10 minute interval and following headers :<br> - <em>date </em>: local date (UTC+01 with daylight saving time)<br> - <em>variable </em>: parameter of interest, with following classes :<br> w_elevation: Water table elevation [m. asl]<br> w_temperature : Groundwater temperature [°C]<br> - <em>name </em>: name of piezometer (see coordinates in GPS_piezometers.zip)<br> - <em>dateUTC </em>: date with UTC timezone</p> <p>Data can be quickly vizualized in<strong> plot_piezo.png</strong> or interactively in a browser using <strong>plot_piezo_interactive.html</strong></p>
Water stable isotope, temperature and electrical conductivity dataset (snow, ice, rain, surface water, groundwater) from a high alpine catchment (2019-2021).
<p>Data collected in the Otemma forefield in Switzerland (45°56’03”N,7°24’42”) from July 2019 to October 2021.<br> Data were collected by the research teams of Bettina Schaefli<sup>2</sup> and Stuart N. Lane<sup>1</sup>.</p> <p><sup>1</sup> Institute of Earth Surface Dynamics (IDYST), University of Lausanne, 1015 Lausanne, Switzerland</p> <p><sup>2</sup> Institute of Geography (GIUB), University of Bern, 3012 Bern, Switzerland</p> <p>For further information, please contact:</p> <ul> <li>tom.muller.1@unil.ch</li> </ul> <p><strong>Description of the dataset</strong></p> <p>This dataset contains water stable isotope (δ<sup>2</sup>H, δ<sup>17</sup>O, δ<sup>18</sup>O), water temperature and water electrical conductivity (EC) measurements collected from the Otemma glacier catchment.</p> <p>All water isotope samples were collected directly from the source and stored in 12 mL amber glass vials with an air-tight caps. River samples were first collected with an automatic ISCO 6712 portable water sampler with 1L open plastic bottles and transferred in 12 mL vials every one to two weeks. All isotope analysis were performed using a Wavelength-Scanned Cavity Ring Down Spectrometer (Picarro 2140-I, Santa Clara, California, USA) and expressed relative to the international Vienna Standard Mean Ocean Water (VSMOW) standards.</p> <p>All EC and water temperature measurements were performed with a WTW Multi 3510 IDS logger with a IDS TetraCon® 925 probe.</p> <p>The dataset contains measurements performed at various locations within the catchment. A total of approximately 1500 measurements are provided. In the dataset each point correspond to a measurement station (column "<strong>Station</strong>") which we classified in specific class of water (column "<strong>Type</strong>") as follows :</p> <ul> <li><strong>Stream </strong>: samples collected at three locations, from the glacier snout, after a small outwash plain and 2km downstream.</li> <li><strong>Tributary </strong>: 5 hillslopes tributaries originating from small seasonal overland flow or small springs at the base of the morainic hillslope. Those tributaries were monitored weekly. In addition, a few other seasonal lateral streams were sampled in various locations (Type: Other tributaries).</li> <li><strong>Bedrock </strong>: A few exfiltrations directly leaking out of the bedrock outcrop were sampled.</li> <li><strong>Ice </strong>: Ice was sampled either as surface ice (small cores 5 cm deep), as deeper cores (5 to 8m deep) or as meltwater from supraglacial gullies. All solid ice samples were melted at ambiant air temperature in air-tight plastic bags before being transferred into 12 mL vials.</li> <li><strong>Snow </strong>: The snowpack was sampled either at the surface (0 to 5cm) or at about 20 cm depth. Where possible, meltwater leaking from the snowpack was sampled. At 3 locations in 2021, we dug snowpits from which we sampled snow at different layers with depth. All solid snow samples were melted at ambiant air temperature in air-tight plastic bags before being transferred into 12 mL vials</li> <li><strong>Rain </strong>: Rainwater was mostly sampled at our camp site at 2450 m. asl. Rainwater samples represent single rain events which are identified by dry periods of at least one day long.</li> <li><strong>Groundwater </strong>: shallow (2 to 3 meters) fully-screened groundwater wells were installed in the outwash plain and water sampled monthly in the snow-free season.</li> </ul> <p>- GPS coordinates are provided with each point (Swiss coordinate system CH1903+ / LV95<strong> (EPSG: 2056)).</strong></p> <p>- Dates are provided in local timezone (GMT+1 with daylight saving time) and in UTC date format.</p> <p>- Analyitcal error from the Picarro spectrometer is reported as 1 standard deviation.</p> <p>More information can be accessed in the corresponding publication by Müller et al. (to be published in 2023).</p> <p><strong>Data files</strong></p> <ul> <li><em>Otemma_isotope_EC_T_2019_2021.csv</em> : file containing all data with GPS coordinates</li> <li> <p><em>isotope_locations_Otemma.jpg</em> : an overview of the locations of each measurement point</p> </li> <li> <p><em>Otemma_Isotopes_2019-2020.html </em>: interactive plots of all datasets (δ<sup>2</sup>H, EC, temperature), classified by Type.</p> </li> </ul>
Nyack Floodplain RiverNet surface water and groundwater dissolved oxygen, conductivity, water level, and temperature Northwest Montana, USA, 2012-2020
Water dissolved oxygen, conductivity, temperature, and level from ten locations in the Nyack Floodplain of the Middle Fork of the Flathead River in Northwest Montana, USA. Measurements are made hourly for the period of 2012 to 2020. Six sensor are placed in groundwater wells and four are placed in surface water. Data up to June 26h, 2019 have been cleaned to remove bad data and flag potentially anomalous observations.
Groundwater well pressure, temperature, conductance, salinity and oxygen measurements for GCE-LTER study hammock HN_i_1 from 30-Oct-2008 to 03-Dec-2013
Groundwater pressure, temperature and other parameters (e.g. conductance, salinity, oxygen and pH) were measured using various instruments installed in PVC wells at the GCE-LTER HN_i_1 holocene study hammock from 30-Oct-2008 to 03-Dec-2013. Observations were logged continuously at 15 minute intervals, and accumulated data were downloaded from loggers using manufacturer-provided communications software semi-monthly, then imported into MATLAB for post-processing, quality control and documention. Raw, unvented pressure readings were corrected for atmospheric pressure and sensor height from the bottom of the well to generate corrected pressure readings. Separate data tables are provided for each combination of instrument and well due to differences in parameters measured and post-processing steps, but all tables include detailed information on location and well characteristics to support integration and analysis. These data were collected as part of the Georgia Coastal Ecosystems LTER Intensive Hammock Characterization and Hammock Groundwater Modeling projects, and will be used for groundwater modeling studies at two marsh hammocks on Sapelo Island, Georgia.
Groundwater well pressure, temperature, conductance, salinity and oxygen measurements for GCE-LTER study hammock PC_i_29 from 15-Aug-2008 to 13-Dec-2013
Groundwater pressure, temperature and other parameters (e.g. conductance, salinity, oxygen and pH) were measured using various instruments installed in PVC wells at the GCE-LTER PC_i_29 pleistocene study hammock from 15-Aug-2008 to 13-Dec-2013. Observations were logged continuously at 15 minute intervals, and accumulated data were downloaded from loggers using manufacturer-provided communications software semi-monthly, then imported into MATLAB for post-processing, quality control and documention. Raw, unvented pressure readings were corrected for atmospheric pressure and sensor height from the bottom of the well to generate corrected pressure readings. Separate data tables are provided for each combination of instrument and well due to differences in parameters measured and post-processing steps, but all tables include detailed information on location and well characteristics to support integration and analysis. These data were collected as part of the Georgia Coastal Ecosystems LTER Intensive Hammock Characterization and Hammock Groundwater Modeling projects, and will be used for groundwater modeling studies at two marsh hammocks on Sapelo Island, Georgia.
Code and data for Mire microclimate: groundwater buffers temperature in waterlogged versus dry soils.
<p>Version of record of the manuscript's code and data, as accepted by the International Journal of Climatology.</p>
Hourly soil moisture, soil temperature, groundwater temperature, and groundwater stage height measurements from 9 Hillslope Study sites located in Macon County, North Carolina, within the Upper Little Tennessee River Basin
The Hillslope Study was established to directly link land use impacts to streamwater quality in the southern Appalachian Mountains. Nine sites were selected in the Little Tennessee River watershed in Macon County, NC, representing four land use types: forest, mountain development, traditional valley, and large river valley. At each of these sites, three subsurface flowpaths were identified, and four plots were established along the flowpath following the elevation gradient. At seven of the nine sites, the three lower elevation plots at one of the subsurface flowpaths had ground water wells installed in order to measure groundwater stage and temperature along an elevational gradient. Additional sensors were installed adjacent to the groundwater wells to measure soil moisture at 0-30 cm and 30-60 cm below the ground surface uphill and downhill of the well, and soil temperature at 5 cm below the ground surface. Measurements were taken every 60 seconds and output as hourly averages. Data were used as part of the Regional HydroEcological Simulation System (RHESSys) ecohydrologic model. Please see the accompanying well construction data for additional groundwater well information.
Multi-year dataset for groundwater level, temperature, and chemical and isotopic compositions of different water bodies in an alpine catchment on the northeastern Qinghai-Tibet Plateau, China
<p>Here we provide the multi-year dataset for groundwater level, temperature, and chemical and isotopic compositions of different water bodies in an alpine catchment on the northeastern Qinghai-Tibet Plateau, China. The first file contains monitoring data, including groundwater levels and ground temperatures. The second file includes the results of the sample analyses as well as the numbers and locations of the sampling sites.</p>
River Erpe (Berlin, Germany) groundwater levels, temperature and 222-radon data set, June 2019
<p>Time series of groundwater levels and temperature, chloride concentrations as well as 222-radon activities in piezometers P0 to P9 and P11 located close to Heidemühle at the River Erpe, Berlin, Germany, collected between June and November 2019. In "Rn_eql_incubations.csv", "mea" denotes the mean activity and "sdd" the associated standard deviation.</p>
Dataset to the article 'Redox-zoning in high-energy subterranean estuaries as a function of storm floods, temperatures, seasonal groundwater recharge and morphodynamics'
<p>This repository contains model input files, and pre- and post-processing scripts for the research article:</p> <p>Janek Greskowiak, Stephan L. Seibert, Vincent E.A. Post, Gudrun Massmann (2023), Redox-zoning in high-energy subterranean estuaries as a function of storm floods, temperatures, seasonal groundwater recharge and morphodynamics, Estuarine, Coastal and Shelf Science, https://doi.org/10.1016/j.ecss.2023.108418</p> <p><br> Data:</p> <p>The folder Laserascannerdata_top_and_hydr_heads contains five cross-shore topography profiles of a high energy beach on Spiekeroog Island, Germany, including a python-script that assembles them to a daily times-series over one year and that calculates the tide-averaged hydraulic heads in the intertidal zone as detailed in Greskowiak and Massmann (2021), The impact of morphodynamics and storm floods on pore water flow and transport in the subterranean estuary, Hydrological Processes, 35:e14050, https://doi.org/10.1002/hyp.14050</p> <p><br> Model input:</p> <p>The file Dynamod_1_redox_basecase.zip contains a folder with the model input textfiles (SEAWAT and PHT3D) for the case that considers all dynamic influence factors investigated in the paper, i.e., seasonal meteoric groundwater recharge, stormfloods, temperature-dependence of reaction rates and morphodynamics.</p> <p>The files pht3d_ph.dat and pht3d_datab.dat are PHT3D model specific files defining the reacants and reactions, and have to be copied into the model folder before PHT3D is started.</p> <p><br> Run models:</p> <p>First the SEAWAT model needs to be run with the name file 'Dynamod_1_redox_basecase.nam'. This creates the mt3d link file 'mt3d_link.ftl'. After that, PHT3D has to be started with the name file 'pht3d.nam'</p> <p>Note that running the models will generate 22 Gybte output.</p> <p><br> Pre-processing:</p> <p>All model input files were generated with the python-script Dynamod_1_redox_basebase.py using Flopy, a python-based groundwater modelling user-interface:<br> https://www.usgs.gov/software/flopy-python-package-creating-running-and-post-processing-modflow-based-models</p> <p><br> Post-processing:</p> <p>For the figures 3,4 and S1, S2 in the paper, the corresponding python scripts are provided in this database. Note that with respect to Figures 5 and S3, only the results for the case with all dynamic influence factors (Figure S3_h) are being plotted.</p> <p> </p> <p>Other model output:<br> Animation_A1_Dynamod_redox.mp4 is a video animation showing the dynamic modelled salinity and temperature distribution, and redox zoning in the subterranean estuary all dynamic influence factors investigated in the paper, i.e., seasonal meteoric groundwater recharge, stormfloods, temperature-dependence of reaction rates and morphodynamics.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.