Released
Dataset

HydReSGeo: Field experiment dataset of surface-sub-surface infiltration dynamics acquired by hydrological, remote sensing, and geophysical measurement techniques

Cite as:

Keller, Sina; Riese, Felix M.; Allroggen, Niklas; Jackisch, Conrad (2020): HydReSGeo: Field experiment dataset of surface-sub-surface infiltration dynamics acquired by hydrological, remote sensing, and geophysical measurement techniques. GFZ Data Services. https://doi.org/10.5880/fidgeo.2020.015

Status

I   N       R   E   V   I   E   W : Keller, Sina; Riese, Felix M.; Allroggen, Niklas; Jackisch, Conrad (2020): HydReSGeo: Field experiment dataset of surface-sub-surface infiltration dynamics acquired by hydrological, remote sensing, and geophysical measurement techniques. GFZ Data Services. https://doi.org/10.5880/fidgeo.2020.015

Abstract

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.

Authors

  • Keller, Sina;Karlsruhe Institute of Technology, Karlsruhe, Germany
  • Riese, Felix M.;Karlsruhe Institute of Technology, Karlsruhe, Germany
  • Allroggen, Niklas;University of Potsdam, Potsdam, Germany
  • Jackisch, Conrad;Technische Universität Braunschweig, Braunschweig, Germany

Contact

Keywords

soil moisture, irrigation experiment, hyperspectral data, VNIR data, ground penetrating radar, LWIR data, interdisciplinary dataset, CAOS, Catchments as Organised Systems

GCMD Science Keywords

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      • publisher: GFZ Data Services
      • publicationYear: 2020
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        • subject: irrigation experiment
        • subject: hyperspectral data
        • subject: VNIR data
        • subject: ground penetrating radar
        • subject: LWIR data
        • subject: interdisciplinary dataset
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          • affiliation: University of Potsdam, Potsdam, Germany
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          • nameIdentifier (nameIdentifierScheme=ORCID): 0000-0001-7389-1201
          • affiliation: Technische Universität Braunschweig, Braunschweig, Germany
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      • language: en
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        • relatedIdentifier (relatedIdentifierType=DOI relationType=Cites): 10.5194/hess-21-3749-2017
        • relatedIdentifier (relatedIdentifierType=URL relationType=Cites): https://isbnsearch.org/isbn/9783879076383
        • relatedIdentifier (relatedIdentifierType=DOI relationType=IsSupplementTo): 10.5194/isprs-annals-IV-1-101-2018
        • relatedIdentifier (relatedIdentifierType=DOI relationType=Cites): 10.5281/zenodo.3576242
        • relatedIdentifier (relatedIdentifierType=DOI relationType=Cites): 10.5281/zenodo.3706418
      • rightsList
        • rights (rightsURI=http://creativecommons.org/licenses/by/4.0/): CC BY 4.0
      • descriptions
        • description (descriptionType=Abstract)
          • br: 
          • br: 
          • br: 
          • br: 
      • geoLocations
        • geoLocation
          • geoLocationPoint
            • pointLongitude: 8.441283
            • pointLatitude: 49.131333
          • geoLocationPlace: The experimental setup consists of 2 x 4 plots, each covering an area of one square meter
      • fundingReferences
        • fundingReference
          • funderName: Deutsche Forschungsgemeinschaft
          • funderIdentifier (funderIdentifierType=Crossref Funder ID): http://doi.org/10.13039/501100001659
          • awardNumber: 1598
          • awardTitle: From Catchments as Organised Systems to Models based on Dynamic Functional Units - CAOS
  • dif:  /  download xml
    • DIF (xsi:schemaLocation=http://gcmd.gsfc.nasa.gov/Aboutus/xml/dif/ http://gcmd.nasa.gov/Aboutus/xml/dif/dif_v9.8.2.xsd)
      • Entry_ID: 10.5880/fidgeo.2020.015
      • Entry_Title: HydReSGeo: Field experiment dataset of surface-sub-surface infiltration dynamics acquired by hydrological, remote sensing, and geophysical measurement techniques
      • Data_Set_Citation
        • Dataset_Creator: Keller, Sina; Riese, Felix M.; Allroggen, Niklas; Jackisch, Conrad
        • Dataset_Title: HydReSGeo: Field experiment dataset of surface-sub-surface infiltration dynamics acquired by hydrological, remote sensing, and geophysical measurement techniques
        • Dataset_Release_Date: 2020
        • Dataset_Release_Place: Potsdam, Germany
        • Dataset_Publisher: GFZ Data Services
        • Online_Resource: http://dx.doi.org/10.5880/fidgeo.2020.015
      • Parameters
        • Category: EARTH SCIENCE
        • Topic: LAND SURFACE
        • Term: SOILS
        • Variable_Level_1: SOIL MOISTURE/WATER CONTENT
      • Parameters
        • Category: EARTH SCIENCE
        • Topic: TERRESTRIAL HYDROSPHERE
        • Term: 
      • Parameters
        • Category: EARTH SCIENCE SERVICES
        • Topic: DATA ANALYSIS AND VISUALIZATION
        • Term: STATISTICAL APPLICATIONS
      • ISO_Topic_Category: geoscientificInformation
      • Keyword: soil moisture
      • Keyword: irrigation experiment
      • Keyword: hyperspectral data
      • Keyword: VNIR data
      • Keyword: ground penetrating radar
      • Keyword: LWIR data
      • Keyword: interdisciplinary dataset
      • Keyword: CAOS
      • Keyword: Catchments as Organised Systems
      • Spatial_Coverage
        • Southernmost_Latitude: 49.131333
        • Northernmost_Latitude: 49.131333
        • Westernmost_Longitude: 8.441283
        • Easternmost_Longitude: 8.441283
      • Data_Center
        • Data_Center_Name
          • Short_Name: Deutsches GeoForschungsZentrum GFZ
          • Long_Name: GFZ
        • Personnel
          • Role: DATA CENTER CONTACT
          • Last_Name: Deutsches GeoForschungsZentrum GFZ
      • Summary
        • Abstract: 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.
      • Metadata_Name: DIF
      • Metadata_Version: 9.8.2
  • escidoc:  /  download xml
    • resource
      • title (xml:lang=en): HydReSGeo: Field experiment dataset of surface-sub-surface infiltration dynamics acquired by hydrological, remote sensing, and geophysical measurement techniques
      • creator
        • creatorName: Keller, Sina
        • givenName: Sina
        • familyName: Keller
        • nameIdentifier (nameIdentifierScheme=ORCID): 0000-0002-7710-5316
        • affiliation: Karlsruhe Institute of Technology, Karlsruhe, Germany
      • creator
        • creatorName: Riese, Felix M.
        • givenName: Felix M.
        • familyName: Riese
        • affiliation: Karlsruhe Institute of Technology, Karlsruhe, Germany
      • creator
        • creatorName: Allroggen, Niklas
        • givenName: Niklas
        • familyName: Allroggen
        • nameIdentifier (nameIdentifierScheme=ORCID): 0000-0002-7030-6457
        • affiliation: University of Potsdam, Potsdam, Germany
      • creator
        • creatorName: Jackisch, Conrad
        • givenName: Conrad
        • familyName: Jackisch
        • nameIdentifier (nameIdentifierScheme=ORCID): 0000-0001-7389-1201
        • affiliation: Technische Universität Braunschweig, Braunschweig, Germany

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