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Preprints
https://doi.org/10.5194/essd-2020-149
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2020-149
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  09 Jul 2020

09 Jul 2020

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This preprint is currently under review for the journal ESSD.

SoilKsatDB: global soil saturated hydraulic conductivity measurements for geoscience applications

Surya Gupta1, Tomislav Hengl2, Peter Lehmann1, Sara Bonetti1, and Dani Or1 Surya Gupta et al.
  • 1Soil and Terrestrial Environmental Physics, Department of Environmental Systems Science, ETH, Zürich, Switzerland
  • 2OpenGeoHub foundation / EnvirometriX, Wageningen, the Netherlands

Abstract. Saturated soil hydraulic conductivity (Ksat) is a key parameter in many hydrological and climatic modeling applications, as it controls the partitioning between precipitation, infiltration and runoff. Ksat values are primarily determined from soil textural properties and soil forming processes, and may vary over several orders of magnitude. Despite availability of Ksat datasets at catchment or regional scale, significant efforts are required to import and bind the data before it could be used for modeling. In this work, a total of 1,910 sites with 13,267 Ksat measurements were assembled from published literature and other sources, standardized, and quality-checked in order to provide a global database of soil saturated hydraulic conductivity (SoilKsatDB). The SoilKsatDB covers most global regions, with the highest data density from the USA, followed by Europe, Asia, South America, Africa, and Australia. In addition to Ksat, other soil variables such as soil texture (11,667 measurements), bulk density (11,151 measurements), soil organic carbon (9,787 measurements), field capacity (7,389) and wilting point (7,418) are also included in the dataset. The results of using the SoilKsatDB to fit Ksat pedotransfer functions (PTFs) for temperate climatic regions and laboratory based soil samples based on soil properties (sand and clay content, bulk density) show that reasonably accurate models can be fitted using Random Forest (best CCC = 0.70 and CCC = 0.73 for temperate and lab based measurements, respectively). However when temperate and laboratory based Ksat PTFs are applied to soil samples from tropical climates and field measurements, respectively, the model performance is significantly lower (CCC = 0.51 for tropical and CCC = 0.13 for field samples). PTFs derived for temperate soils and laboratory measurements might not be suitable for estimating Ksat for tropical regions or field measurements, respectively. The SoilKsatDB dataset is available at https://doi.org/10.5281/zenodo.3752721 and the code used to produce the compilation is publicly available under an open data license.

Surya Gupta et al.

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SoilKsatDB: a global compilation of soil saturated hydraulic conductivity measurements, S. Gupta, T. Hengl, P.Lehmann, S. Bonetti, and D. Or https://doi.org/10.5281/zenodo.3752722

Surya Gupta et al.

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