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dc.contributor.author
Gupta, Surya
dc.contributor.author
Hengl, Tomislav
dc.contributor.author
Lehmann, Peter
dc.contributor.author
Bonetti, Sara
dc.contributor.author
Or, Dani
dc.date.accessioned
2021-04-23T06:05:53Z
dc.date.available
2021-04-23T03:09:10Z
dc.date.available
2021-04-23T06:05:53Z
dc.date.issued
2021-04-15
dc.identifier.issn
1866-3516
dc.identifier.issn
1866-3508
dc.identifier.other
10.5194/essd-13-1593-2021
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/480153
dc.identifier.doi
10.3929/ethz-b-000480153
dc.description.abstract
The saturated soil hydraulic conductivity (Ksat) is a key parameter in many hydrological and climate models. Ksat values are primarily determined from basic soil properties and may vary over several orders of magnitude. Despite the availability of Ksat datasets in the literature, significant efforts are required to combine the data before they can be used for specific applications. In this work, a total of 13 258Ksat measurements from 1908 sites were assembled from the published literature and other sources, standardized (i.e., units made identical), and quality checked in order to obtain a global database of soil saturated hydraulic conductivity (SoilKsatDB). The SoilKsatDB covers most regions across the globe, with the highest number of Ksat measurements from North America, followed by Europe, Asia, South America, Africa, and Australia. In addition toKsat, other soil variables such as soil texture (11 584 measurements), bulk density (11 262 measurements), soil organic carbon (9787 measurements), moisture content at field capacity (7382), and wilting point (7411) are also included in the dataset. To show an application of SoilKsatDB, we derived Ksat pedotransfer functions (PTFs) for temperate regions and laboratory-based soil properties (sand and clay content, bulk density). Accurate models can be fitted using a random forest machine learning algorithm (best concordance correlation coefficient (CCC) equal to 0.74 and 0.72 for temperate area and laboratory measurements, respectively). However, when these Ksat PTFs are applied to soil samples obtained from tropical climates and field measurements, respectively, the model performance is significantly lower (CCCD0.49 for tropical and CCCD0.10 for field measurements). These results indicate that there are significant differences between Ksat data collected in temperate and tropical regions and Ksat measured in the laboratory or field. The SoilKsatDB dataset is available at https://doi.org/10.5281/zenodo.3752721 (Gupta et al., 2020) and the code used to extract the data from the literature and the applied random forest machine learning approach are publicly available under an open data license.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Copernicus
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.title
SoilKsatDB: Global database of soil saturated hydraulic conductivity measurements for geoscience applications
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
ethz.journal.title
Earth System Science Data
ethz.journal.volume
13
en_US
ethz.journal.issue
4
en_US
ethz.journal.abbreviated
Earth Syst. Sci. Data
ethz.pages.start
1593
en_US
ethz.pages.end
1612
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Göttingen
en_US
ethz.publication.status
published
en_US
ethz.date.deposited
2021-04-23T03:09:14Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2021-04-23T06:06:05Z
ethz.rosetta.lastUpdated
2022-03-29T06:43:38Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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