This dataset consists of spatially and temporally resolved data of dye-infiltration patterns, earthworms and macropores as well as supporting data, such as land use, soil moisture content, soil temperature, bulk density, and soil texture, in the Wollefsbach area of the Attert Catchment in Luxembourg (Pfister et al., 2005).The data was gathered in six measurement campaigns in the period from May 2015 to March 2016. During each measurement campaign we measured at five random sites on each of six chosen fields: three grasslands and three agricultural fields. At each measurement site a combination of measurements was performed: infiltration patterns of blue stained water, earthworm abundance (species level), macropore counts on horizontal soil profiles (in three depths, discriminating three size classes and stained or non-stained), soil temperature and moisture contents in three depths. Finally, undisturbed soil core samples were taken during one campaign for the determination of the texture and bulk density at different sampling sites. In the data table we also include GIS derived values of elevation, slope, aspect, heat load index, and topographical wetness index. Details on all the measurement methods, GIS-analysis methods and units of the data are given below.This data was gathered as part of the Joint Research Project “Catchments as Organised Systems” (CAOS, Zehe et al., 2014) funded by the German Research Foundation.---------------------------------------------------Version history:10 February 2020, release of Version 1.1.:The authors discovered that some rows in the data table “Earthworms_Macropores_Data.csv” for September Field 3 and Field 4 were accidentally exchanged. Compared to version 1.0, the data in rows 71 to 75 (Sept_3_1 to Sept_3_5) were exchanged with the data in rows 76 to 80 (Sept_4_1 to Sept_4_5). The authors apologise for this and ask everyone who downloaded the data of version 1.0 are advised to only use version 1.1, because there was an error which could lead to wrong results. Nevertheless, version 1.0 of the data table is available in the "previous-versions" subfolder via the Data Download link. The infiltration data included in “2019-022_vanSchaik-et-al_Infiltration_patterns.zip” remain unchanged.
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 Regional Research Network „Water in Central Asia“ (CAWa) funded by the German Federal Foreign Office consists of 19 remotely operated multi-parameter stations (ROMPS) in Central Asia. These stations were installed by the German Research Centre for Geosciences (GFZ) in Potsdam, Germany in close cooperation with the Central-Asian Institute for Applied Geosciences (CAIAG) in Bishkek, Kyrgyzstan, the national hydrometeorological services in Uzbekistan and Tajikistan, the Ulugh Beg Astronomical Institute in Tashkent, Uzbekistan, and the Kabul Polytechnic University, Afghanistan.
The primary objective of these stations is to support the establishment of a reliable data basis of meteorological and hydrological data especially in remote areas with extreme climate conditions in Central Asia for applications in climate and water monitoring. Up to now, ten years of data are provided for an area of scarce station distribution and with limited open access data which can be used for a wide range of scientific or engineering applications.
This dataset provides different types of raw hydrometeorological data such as air temperature, relative humidity, air pressure, wind speed and direction, precipitation, solar radiation, soil moisture and soil temperature as well as snow parameters and river discharge information for selected sites. The data has not undergone any quality control mechanism and should, therefore, be seen as raw data. A visual inspection of the data set has been made and some errors and quality degradation are listed in Zech et al. (2020) but does not claim to be complete. A quality control is strongly recommended by the authors before using the data.
Each station data has its own storage directory at the data dissemination server named with the abbreviation (4-letter code) of the station. The data is sampled with a 5-minute interval and stored in hourly files separated by the type of data. These files are then archived as monthly files named with the station abbreviation, type of data, year and month. After one year, these monthly files are further archived to a yearly file. A detailed description for the stations is provided by the Station Exposure Descriptions. Further information about the dataset can be found in Zech et al. (2020). All data is compiled as ASCII data in two different formats which are explained in the documents GITW-SSP-FMT-GFZ-003.pdf (for the stations ALAI, ALA6, and SARY) and CAWA-SSP-FMT-GFZ-006.pdf (for all other stations).
Monthly, the data will be dynamically extended as long as data can be acquired from the stations. Additionally, the near real-time data can be displayed and downloaded without any registration from the Sensor Data Storage System (SDSS) hosted at the Central-Asian Institute for Applied Geosciences (CAIAG) in Bishkek, Kyrgyzstan.