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The data set was collected to identify hydrological processes and their evolution over it time. It consists of several individual files in tabstop delimeted text format. The data set contains the data obtained from deuterium and brilliant blue tracer experiments at two chronosequence studies in the glacier forefield of the Stone Glacier and the Griessfirn in the central Alps, Switzerland. Each chronosequence consisted of four moraines of different ages (from 30 to 13500 years). At each forefield sprinkling experiments with deuterium and dye tracer experiments with blue dye (Brilliant Blue) were conducted on three plots per moraine. The moraines at the forefield of the Stone Glacier developed from siliceous parent material and at the forefield of the Griessfirn from calcareous parent material. Data from the siliceous forefield are marked with (S) and data from the calcareous forefield are marked with (C). The data set consist of soil moisture time series and soil water isotope profiles of the sprinkling experiments with deuterium, as well as trinary images of stained vertical subsurface flow paths from the dye tracer experiment. The individual plots per moraine are distinguished via their position relative to one another on the moraine (left, middle, and right, looking upslope). The plots used for the sprinkling experiments were located in close vicinity to the plots used for the dye tracer experiments. For the sprinkling experiments with deuterium each plot (4m x 6m) per age class was equipped with 6 soil moisture sensors. Three of these sensors were installed as a sensor profile at one side of the plot about one meter downslope from the upper plot boundary. The sensors were installed at 10, 30, and 50 cm soil depth. On the other side of the plot, two sensors were placed in 10 cm depth, one opposite to the sensor profile and the second sensor one meter upslope from the lower plot boundary. The sixth sensor was placed at 10 cm depth in the center of the plot. The plots were irrigated on three consecutive days with three different irrigation intensities and deuterium concentrations. Per forefield, the soil moisture data are listed in one file per age class. The file contains for each plot, the time stamp and the soil moisture values of the 6 sensors.
The data set contains hydrological, meteorological and gravity time series collected at Argentine-German Geodetic Observatory (AGGO) in La Plata, Argentina. The hydrological series include soil moisture, temperature, electric conductivity, soil parameters, and groundwater variation. The meteorological time series comprise air temperature, humidity, pressure, wind speed, solar short- and long-waver radiation, and precipitation. The observed hydrometeorological parameters are extended by modelled value of evapotranspiration and water content variation in the zone between deepest soil moisture sensor and the groundwater level. Gravity products include large-scale hydrological, oceanic as well as atmospheric effects. These gravity effects are furthermore extended by local hydrological effects and gravity residuals suitable for comparison and evaluation of the model performance. Provided are directly observed values denoted as Level 1 product along with pre-processed series corrected for known issues (Level 2). Level 3 products are model outputs acquired using Level 2 data. The maximal temporal coverage of the data set ranges from May 2016 up to November 2018 with some exceptions for sensors and models set up in May 2017. The data set is organized in a database structure suitable for implementation in a relational database management system. All definitions and data tables are provided in separate text files allowing for traditional use without database installation.Software related to the data acquisition, processing, and modelling can be found in a separate publication describing scripts applied to the data set presented here. The software publication is available at https://doi.org/10.5880/GFZ.5.4.2018.002 (Mikolaj, 2018)
This software publication describes the data acquisition, processing and modelling of hydrological, meteorological and gravity time series prepared for the Argentine-German Geodetic Observatory (AGGO) in La Plata, Argentina. The corresponding output data set is available at http://doi.org/10.5880/GFZ.5.4.2018.001 (Mikolaj et al., 2018).Processed hydrological series include soil moisture, temperature, electric conductivity, and groundwater variation. The processed meteorological time series comprise air temperature, humidity, pressure, wind speed, solar short- and long-waver radiation, and precipitation. Modelling scripts include evapotranspiration, combined precipitation, and water content variation in the zone between deepest soil moisture sensor and groundwater. In addition, large-scale hydrological, oceanic as well as atmospheric effect are modelled along with the local hydrological effects. To allow for a comparison of the model outputs to observations, processing script of gravity residuals is provided as well.
The described dataset was the result of a field effort consisting of several campaigns to assess the influence of carbon increase as a result of agroforestry treatments on soil hydrological characteristics and water fluxes at two sites in Malawi. At the sites, two experimental trials have been established which differ in age and soil characteristics, while climatic conditions are roughly comparable. At both sites we focused on control plots of maize and agroforestry treatments including Gliricidia sepium (Jacq.) Walp. as the tree component. The dataset contains soil characteristics such as texture, porosity, carbon and nitrogen concentrations, carbon density fractions, dispersible clay proportions, soil hydraulic conductivity and water retention curves. To assess the differences in water fluxes between treatments and sites, we installed soil moisture and matric potential sensors and a small weather station at the sites and monitored the fluxes over the course of about three months. The resulting time series are also part of the dataset, as well as some measurements of maize heights. The file structure of the dataset as well as details on the sites, sampling procedures, measurements and methodology are included in the data description.
The Sassen BF1 soil moisture station is part of an agrometeorological test site and aims at supplying environmental data for algorithm development in remote sensing and environmental modelling, with a focus on soil moisture and evapotranspiration.The site is intensively used for practical tests of remote sensing data integration in agricultural land management practices. First measurement infrastructure was installed by DLR in 1999 and instrumentation was intensified in 2011 and later as the site became part of the TERENO-NE observatory. The soil moisture station station Sassen BF1 was installed in 2012. It is located next to a pylon on a crest of an undulating field. The station is equipped with sensor for measuring the following variables: ScemeSpadeSoilMoisture_Spade_2_Temperature, ScemeSpadeSoilMoisture_Spade_6_Temperature, ScemeSpadeSoilMoisture_Spade_1, ScemeSpadeSoilMoisture_Spade_2, ScemeSpadeSoilMoisture_Spade_3, ScemeSpadeSoilMoisture_Spade_4, ScemeSpadeSoilMoisture_Spade_5 and ScemeSpadeSoilMoisture_Spade_6. The current version of this dataset is 1.5. This version includes two additional years of data (from-year to-year)and a revised version of the data flags. New authors were added for this new version: Alice Künzel (GFZ Potsdam), Christian Budach (GFZ Potsdam), Nils Brinckmann (GFZ Potsdam), Max Wegener (DLR Neustrelitz) and Klemens Schmidt (DLR Neustrelitz).A detailed overview on all changes is provided in the station description file. Older versions are available in the 'previous_versions' subfolder via the Data Download link. A first version of this data was provided under http://doi.org/ containing the measured data only. The dataset is also available through the TERENO Data Discovery Portal. The datafile will be extended once per year as more data is acquired at the stations and the metadatafile will be updated. New columns for new variables will be added as necessary. In case of changes in data processing, which will result in changes of historical data, an new Version of this dataset will be published using a new doi. New data will be added after a delay of several months to allow manual interference with the quality control process. During October 2020 a Bug in the published data was detected and a new version of the datasets was released from beginning until mid 2020. Data processing was done using DMRP version: 1.8.4. Metadataprocessing was done using DMETA version: 1.2.0.
The described dataset resulted from a joint multidisciplinary measurement campaign in an agroforestry system in the Western Cape region in South Africa. Five participating institutions measured a range of environmental variables to characterise the influence of windbreak trees onto water fluxes, nutrient distribution and microclimate in the adjacent blackberry field. The dataset contains spatially collected soil characteristics, a soil profile description, time series of meteorological measurements as well as soil moisture and matric potential, information on soil hydraulic properties of the soil determined in the laboratory and windbreak characteristics and shape from a point cloud derived from terrestrial LiDAR scanning.
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