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11 results for “Groundwater Table”
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>
Baltimore Ecosystem Study: Long-Term Monitoring of Riparian Water Table Depth and Groundwater Chemistry
Long-term monitoring of riparian water tables and groundwater chemistry began in 2000 along four first or second order steams in and around the Gwynns Falls watershed in Baltimore City and County, MD. One site (Oregon Ridge) is in the completely forested Pond Branch catchment that serves as a ""reference"" study area for the Baltimore LTER (BES). Two sites (Glyndon, Gwynbrook) were in suburban areas of the watershed; one just upstream from the Glyndon BES long-term stream monitoring site in the headwaters of the Gwynns Falls, and one along a tributary that enters the Gwynns Falls just above the Gwynnbrook BES long-term stream monitoring site farther downstream. The final, urban site (Cahill) was along a tributary to the Gwynns Falls in Leakin Park in the urban core of the watershed. Water table data and more detailed descriptions of soils, vegetation, stream channel properties and microbial processes at these sites can be found in Groffman et al. (2002, Environmental Science and Technology 36:4547-4552) and Gift et al. (2010, Restoration Ecology 18:113-120).
Groundwater level data, aquifer system boundaries, and supplementary tables associated with Jasechko, S. et al. Rapid groundwater decline and some cases of recovery in aquifers globally. Nature, doi.org/10.1038/s41586-023-06879-8 (2024).
<p>Groundwater level data, aquifer system boundaries, and Supplementary Tables associated with Jasechko, S., Seybold, H., Perrone, D., Fan, Y., Shamsudduha, M., Taylor, R.G., Fallatah, O., Kirchner, J.W. Rapid groundwater decline and some cases of recovery in aquifers globally. Nature, https://doi.org/10.1038/s41586-023-06879-8 (2024).</p>
Interpolated depth to water table (groundwater) maps for the continental United States
<p><strong>DATA:</strong></p> <p>This is a collection of depth to water table maps with uncertainty estimates for the continental United States for years 1989 and 2019. Data used to create these maps were obtained from the National Ground-Water Monitoring Network (NGWMN). Data included 14,351 sites and 17,632,047 observations for the years 1989-2019. To improve our inference a set of auxiliary variables proven to have a relation with depth to water table were included. We paired point estimates of depth to water table data with environmental data, as well as terrain variables derived out of a base digital elevation model (DEM) created by NASA at a 1x1km resolution. Climatic layers (temperature, precipitation, and snow melt equivalent) for 1989-2019 were obtained from Daymet (Version 4), which provides a continuous grid of historical monthly and annual weather data, with a 1x1km spatial resolution (Thornton et al., 2020). Out of the DEM, primary (slope, aspect) and secondary terrain attributes (curvatures, upslope contributing areas) were used to calculate a compound topographic index (CTI). </p> <p> </p> <p><strong>MODELING FRAMEWORK:</strong></p> <p>Water table depth analyses were conducted using a three-step interpolation approach: 1) we utilized gradient boosted regression trees (GBRT) to make predictions, 2) we used kriging interpolation on GBRT residuals to reduce bias from spatial autocorrelation, to incorporate a spatial correlation structure and to create uncertainty maps, and 3) we then combined the GBRT and kriging predictions for the final map. This method is equivalent to a Universal Kriging, where in our case, we evaluated the trend using GBRT. Model metrics were calculated for the training (80% of the data) and validation (20% of the data) datasets to evaluate overall performance.</p> <p>*** Uncertainty is greater surrounding the 1989 interpolations due to a lower number of observations.</p>
The observed data used in paper titled "A hydrographic method to identify groundwater net recharge, barometric effect, and evapotranspiration from a complicated semidiurnal water table fluctuation"
<p>The water level and atmospheric pressure within the monitoring well located the semi-arid loess hilly-gully region on the piedmont of western Shaanxi Province, China (34°18′36″ N, 107°07′55″ E), were automatically monitored at 20-min intervals by the Levelogger and Barologger, respectively. These data were used as a case example to state a method of estimating groundwater net recharge rate, barometric efficiency and hourly-scaled groundwater evapotranspiration rate.</p>
Data: On the role of water table depth, and urban and vegetation cover on groundwater dry period susceptibility
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Marcell Experimental Forest site, station Watershed S2, groundwater deepwell #202, study of water table elevation above mean sea level in units of meter on a monthly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Marcell Experimental Forest (MAR) contains water table elevation above mean sea level measurements in meter units and were aggregated to a monthly timescale.
Marcell Experimental Forest site, station Watershed S2, groundwater deepwell #202, study of water table elevation above mean sea level in units of meter on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Marcell Experimental Forest (MAR) contains water table elevation above mean sea level measurements in meter units and were aggregated to a yearly timescale.
Supplementary tables for Water Geochemistry and Stable Isotope Changes Record Groundwater Mixing After a Regional Earthquake in Northeast India
<p>This is the supplementary material for <strong>Water Geochemistry and Stable Isotope Changes Record Groundwater Mixing After a Regional Earthquake in Northeast India</strong></p>
Data from: On the role of water table depth and urbanization on groundwater drought susceptibility
<p>Propagation of meteorological drought to groundwater drought is mediated by a range of natural and human-induced drivers. Using long-term (1978–2020)<em> in-situ</em> groundwater level depth (GWD) time series from 2,928 pairs of monitoring wells, this study assesses the role of two such drivers, viz., GWD and urbanization, on groundwater drought characteristics. Results show that locations with deeper GWD often experience less frequent but more intense groundwater droughts with longer average duration. In contrast, urbanization is generally associated with a reduction in groundwater drought duration and an increase in its frequency. Relative to the influence of GWD, urbanization's imprint on groundwater drought characteristics is muted. These findings can aid in improved assessment of groundwater drought risks, and for devising more effective drought adaptation measures.</p>
Data from: On the role of water table depth and urbanization on groundwater drought susceptibility
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