Articles | Volume 10, issue 2
https://doi.org/10.5194/soil-10-587-2024
https://doi.org/10.5194/soil-10-587-2024
Original research article
 | 
09 Sep 2024
Original research article |  | 09 Sep 2024

Addressing soil data needs and data gaps in catchment-scale environmental modelling: the European perspective

Brigitta Szabó, Piroska Kassai, Svajunas Plunge, Attila Nemes, Péter Braun, Michael Strauch, Felix Witing, János Mészáros, and Natalja Čerkasova

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Cited articles

Abbaspour, K. C., AshrafVaghefi, S., Yang, H., and Srinivasan, R.: Global soil, landuse, evapotranspiration, historical and future weather databases for SWAT Applications, Sci. Data, 6, 263, https://doi.org/10.1038/s41597-019-0282-4, 2019. 
Alexander, E. B.: Bulk Densities of California Soils in Relation to Other Soil Properties, Soil Sci. Soc. Am. J., 44, 689–692, https://doi.org/10.2136/sssaj1980.03615995004400040005x, 1980. 
Amorim, H. C. S., Hurtarte, L. C. C., Souza, I. F., and Zinn, Y. L.: C:N ratios of bulk soils and particle-size fractions: Global trends and major drivers, Geoderma, 425, 116026, https://doi.org/10.1016/j.geoderma.2022.116026, 2022. 
Arnold, J. G., Kiniry, J. R., Srinivasan, R., Williams, J. R., Haney, E. B., and Neitsch, S. L.: Soil and Water Assessment Tool: Input/Output Documentation. Version 2012. TR-439, Texas Water Resources Institute, College Station, 1–654, https://swatplus.gitbook.io/io-docs/ (last access: 2 September 2024), 2012. 
Assouline, S. and Or, D.: The concept of field capacity revisited: Defining intrinsic static and dynamic criteria for soil internal drainage dynamics, Water Resour. Res., 50, 4787–4802, https://doi.org/10.1002/2014WR015475, 2014. 
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Short summary
This research introduces methods and tools for obtaining soil input data in European case studies for environmental models like SWAT+. With various available soil datasets and prediction methods, determining the most suitable is challenging. The study aims to (i) catalogue open-access datasets and prediction methods for Europe, (ii) demonstrate and quantify differences between prediction approaches, and (iii) offer a comprehensive workflow with open-source R codes for deriving missing soil data.