10.5880/fidgeo.2020.015 Keller, Sina Sina Keller 0000-0002-7710-5316 Karlsruhe Institute of Technology, Karlsruhe, Germany Riese, Felix M. Felix M. Riese Karlsruhe Institute of Technology, Karlsruhe, Germany Allroggen, Niklas Niklas Allroggen 0000-0002-7030-6457 University of Potsdam, Potsdam, Germany Jackisch, Conrad Conrad Jackisch 0000-0001-7389-1201 Technische Universität Braunschweig, Braunschweig, Germany GFZ Data Services 2020 soil moisture irrigation experiment hyperspectral data VNIR data ground penetrating radar LWIR data interdisciplinary dataset CAOS Catchments as Organised Systems Earth Remote Sensing Instruments > Active Remote Sensing Earth Remote Sensing Instruments > Active Remote Sensing > Profilers/Sounders > Radar Sounders Earth Remote Sensing Instruments > Passive Remote Sensing > Spectrometers/Radiometers > Hyperspectral Spectrometers/Radiometers Earth Remote Sensing Instruments > Passive Remote Sensing > Thermal/Radiation Detectors Earth Remote Sensing Instruments > Passive Remote Sensing > Thermal/Radiation Detectors > FLIR EARTH SCIENCE > LAND SURFACE > SOILS > SOIL MOISTURE/WATER CONTENT EARTH SCIENCE > TERRESTRIAL HYDROSPHERE EARTH SCIENCE SERVICES > DATA ANALYSIS AND VISUALIZATION > STATISTICAL APPLICATIONS In Situ/Laboratory Instruments > Probes > SOIL MOISTURE PROBE Keller, Sina Sina Keller 0000-0002-7710-5316 Karlsruhe Institute of Technology, Karlsruhe, Germany Keller, Sina Sina Keller 0000-0002-7710-5316 Karlsruhe Institute of Technology, Karlsruhe, Germany Allroggen, Niklas Niklas Allroggen 0000-0002-7030-6457 University of Potsdam, Potsdam, Germany Jackisch, Conrad Conrad Jackisch 0000-0001-7389-1201 Technische Universität Braunschweig, Braunschweig, Germany Keller, Sina Karlsruhe Institute of Technology, Karlsruhe, Germany Allroggen, Niklas University of Potsdam, Potsdam, Germany Jackisch, Conrad Technische Universität Braunschweig, Braunschweig, Germany 2017-08-15/2017-08-21 Dataset https://www.dgpf.de/src/tagung/jt2018/proceedings/proceedings/papers/07_PFGK18_Keller_et_al.pdf 10.1109/WHISPERS.2018.8747076 10.1109/IWAGPR.2017.7996067 10.1109/TGRS.2010.2048332 https://seg.org/Portals/0/SEG/News%20and%20Resources/Technical%20Standards/seg_y_rev2_0-mar2017.pdf 10.5194/hess-21-3749-2017 https://isbnsearch.org/isbn/9783879076383 10.5194/isprs-annals-IV-1-101-2018 10.5281/zenodo.3576242 10.5281/zenodo.3706418 CC BY 4.0 This dataset comprises data of an interdisciplinary pedon-scale irrigation experiment at a grassland site near Karlsruhe, Germany, including pedo-hydrological, geophysical, and remote sensing data. The objective of this experiment is to monitor soil moisture dynamics during a well-defined infiltration process with a combination of direct and non-invasive techniques.


Overall, the quantification of soil water dynamics and, in particular, its spatial distributions is essential for the understanding of land-atmosphere interactions. However, the precise measurement of soil water dynamics and its spatial distribution in a continuous manner is a challenging task. Pedo-hydrological monitoring techniques rely on direct, point-based measurement with buried probes for soil water content and matric potential. Non-invasive remote sensing (RS) and geophysical measurement techniques allow for spatially continuous measurements on different spatial scales and extents. This experiment provides a basis for the analyses of signal coherence between the measurement techniques and disciplines. It contributes to forthcoming developments of monitoring setups and modeling approaches to landscape-water dynamics.


For direct monitoring, an array of time-domain reflectometry (TDR) probes and tensiometers was used. As non-invasive techniques, we applied a ground-penetrating radar (GPR), a hyperspectral snapshot sensor, a long-wave infrared (LWIR) sensor, and a hyperspectral field spectroradiometer. We provide the data in nearly raw format, including information about the site properties and calibration references. The data are organized along with the different sensors and disciplines. Thus, the distinct sensor data can also be used independently of each other. In addition, exemplary scripts for reading and processing the data are included.
The experimental setup consists of 2 x 4 plots, each covering an area of one square meter 8.44128 49.1313 Deutsche Forschungsgemeinschaft http://doi.org/10.13039/501100001659 1598 From Catchments as Organised Systems to Models based on Dynamic Functional Units - CAOS