A total of 13,258 Ksat measurements from 1,908 sites were assembled from the published literature and other sources, standardized, and quality-checked in order to obtain a global database of soil saturated hydraulic conductivity (SoilKsatDB). The SoilKsatDB covers most global regions, with the highest data density from North America, followed by Europe, Asia, South America, Africa, and Australia. In addition to Ksat, other soil variables such as soil texture (11,584 measurements), bulk density (11,262 measurements), soil organic carbon (9,787 measurements), field capacity (7,382) and wilting point (7,411) are also included in the data set. To cite this dataset please use: Gupta, S., Hengl, T., Lehmann, P., Bonetti, S., and Or, D.: SoilKsatDB: global soil saturated hydraulic conductivity measurements for geoscience applications, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-149, in review, 2021. Examples of using the SoilKsatDB to generate global maps of Ksat can be found in: Gupta, S., Hengl, T., Lehmann, P., Bonetti, S., Papritz, A. and Or, D. (2021): Global prediction of soil saturated hydraulic conductivity using random forest in a Covariate-based Geo Transfer Functions (CoGTF) framework. accepted for publication in Journal of Advances in Modeling Earth Systems (JAMES). Importing and binding steps are described in detail here. To report an issue or bug please use this link. Ksat data tutorial explaining how to access and use data is available here. In the following, we introduce two different file packages, one for the soil saturated hydraulic conductivity (“sol_ksat”) and another one collecting additional soil hydraulic properties (“sol_hydro”) as well that will be extended in the near future. Note that the package “sol_hydro” is not related to the publication listed above (Gupta et al., 2021a). Description of the files: The datasets in this repository include: sol_ksat.pnts_horizons.***: provides a global compilation of Ksat values and the information described in Table 2 in Gupta et al., (2020). This data is provided in three different data formats. sol_ksat.pnts_horizons.arff, sol_ksat.pnts_horizons.csv.gz, sol_ksat.pnts_horizons.rds, sol_ksat.pnts_metadata_cl_pedo.csv: provides meta-information with Ksat methods and information of estimated soil pedologic unit and climatic region for each Ksat sample. sol_ksat.points_horizons_rm.rds: All ksat values overlaid on climatic, topographic, and vegetation based remote sensing data and extracted the corresponding values. These datasets can be used for spatial modeling for the future. In addition to Ksat points, add these files here as well for the reader that is interested in this topic. sol_hydro.pnts_horizons.***: provides water retention curve values and other soil hydraulic properties. This data is provided in three different data formats. sol_hydro.pnts_horizons.arff, sol_hydro.pnts_horizons.csv.gz, sol_hydro.pnts_horizons.rds, sol_hydro.pnts_horizons_rm.rds: All soil hydraulic values overlaid on climatic, topographic, and vegetation based remote sensing data and extracted the corresponding values. These datasets can be used for spatial modeling for the future. SoilKsatDB is available in CSV, ARFF and RDS formats. ARFF was prepared using the farff package for R. ARFF' (Attribute-Relation File Format) files are like 'CSV' files, with a little bit of added meta information in a header and standardized NA values. Column codes are based on the National Cooperative Soil Survey (NCSS) Soil Characterization Database naming convention (see "README.pdf" for explanation of codes). The SoilKsatDB is a compilation of numerous existing datasets from which the most significant: SWIG data set (Rahmati et al., 2018), UNSODA (Leij et al., 1996), and HYBRAS (Ottoni et al., 2018). Full list of data sources for Ksat data is available in Gupta et al (2021) and in the Readme.pdf.

{"references": ["Leij, F., Alves, W., Van Genuchten, M. T., and Williams, J.: The UNSODA Unsaturated Soil Hydraulic Database; User's Manual, Version 1.0, Rep. EPA/600/R-96, 95, 103, 1996.", "Rahmati, M., Weiherm\u00fcller, L., Vanderborght, J., Pachepsky, Y. A., Mao, L., Sadeghi, S. H., Moosavi, N., Kheirfam, H., Montzka, C., Van Looy, K., et al.: Development and analysis of the Soil Water Infiltration Global database, 2018.", "Ottoni, M. V., Ottoni Filho, T. B., Schaap, M. G., Lopes-Assad, M. L. R., and Rotunno Filho, O. C.: Hydrophysical database for Brazilian soils (HYBRAS) and pedotransfer functions for water retention, Vadose Zone Journal, 17, 2018."]}

This study was supported by ETH Zurich (Grant ETH-18 18-1).