Articles | Volume 10, issue 2
https://doi.org/10.5194/soil-10-587-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/soil-10-587-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Original research article
| 
09 Sep 2024
Original research article |
| 09 Sep 2024
| 09 Sep 2024
Addressing soil data needs and data gaps in catchment-scale environmental modelling: the European perspective
Brigitta Szabó
CORRESPONDING AUTHOR
Institute for Soil Sciences, HUN-REN Centre for Agricultural Research, Budapest, 1022, Hungary
National Laboratory for Water Science and Water Security, Budapest, 1022, Hungary
Piroska Kassai
CORRESPONDING AUTHOR
Institute for Soil Sciences, HUN-REN Centre for Agricultural Research, Budapest, 1022, Hungary
National Laboratory for Water Science and Water Security, Budapest, 1022, Hungary
Svajunas Plunge
Department of Hydrology, Meteorology, and Water Management, Institute of Environmental Engineering, Warsaw University of Life Sciences, Warsaw, 0-653, Poland
Attila Nemes
Department of Hydrology and Water Environment, Division of Environment and Natural Resources, Norwegian Institute of Bioeconomy Research, Ås, 1431, Norway
Péter Braun
Institute for Soil Sciences, HUN-REN Centre for Agricultural Research, Budapest, 1022, Hungary
National Laboratory for Water Science and Water Security, Budapest, 1022, Hungary
Marine Research Institute, Klaipeda University, Klaipeda, 92294, Lithuania
Michael Strauch
Helmholtz Centre for Environmental Research GmbH – UFZ, Department of Computational Landscape Ecology, 04318 Leipzig, Germany
Felix Witing
Helmholtz Centre for Environmental Research GmbH – UFZ, Department of Computational Landscape Ecology, 04318 Leipzig, Germany
János Mészáros
Institute for Soil Sciences, HUN-REN Centre for Agricultural Research, Budapest, 1022, Hungary
National Laboratory for Water Science and Water Security, Budapest, 1022, Hungary
Natalja Čerkasova
Marine Research Institute, Klaipeda University, Klaipeda, 92294, Lithuania
Texas A&M AgriLife, Blackland Research and Extension Center, Temple, TX 76502, USA
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Cited
10 citations as recorded by crossref.
- Development of a harmonized map of soils and soil hydraulic properties for the Po Plain- Northern Italy S. Cazzaniga et al. https://doi.org/10.1016/j.ejrh.2026.103488
- The impact of soil data on SWAT modeling: Effects, requirements, and future directions Y. Bouslihim et al. https://doi.org/10.1016/j.sciaf.2025.e02694
- Exploring Hydrological Response to Land Use/Land Cover Change Using the SWAT+ Model in the İznik Lake Watershed, Türkiye A. Tezel et al. https://doi.org/10.3390/w17131924
- Adjusting Bulk Density Observations in the Hungarian Soil Information and Monitoring System Using Pedotransfer Functions S. Sohrab et al. https://doi.org/10.1111/ejss.70245
- Deep exploration of soil temperature and moisture dynamics in Europe from surface to depth in the era of global warming R. Sarli et al. https://doi.org/10.1016/j.geodrs.2026.e01111
- Leveraging soil diversity to mitigate hydrological extremes with nature-based solutions in productive catchments: an application and insights into the way forward B. Guillaume et al. https://doi.org/10.5194/hess-29-4661-2025
- Prediction of the spatial distribution of soil organic carbon content in Central European agriculturally used peatlands: a case study of the Grójec Valley, Central Poland S. Pindral et al. https://doi.org/10.1007/s11368-026-04271-3
- Педотрансферні функції фізичних властивостей ґрунтів: методологічні підходи до розроблення, каталог моделей та схеми локальної валідації О. Бігун https://doi.org/10.31073/acss100-02
- NoahPy: a differentiable Noah land surface model for simulating permafrost thermo-hydrology W. Tian et al. https://doi.org/10.5194/gmd-19-57-2026
- Applicability-aware inference of salinisation-metal risk associations from sparse soil data Q. Ma et al. https://doi.org/10.1016/j.geoderma.2026.118057
10 citations as recorded by crossref.
- Development of a harmonized map of soils and soil hydraulic properties for the Po Plain- Northern Italy S. Cazzaniga et al. https://doi.org/10.1016/j.ejrh.2026.103488
- The impact of soil data on SWAT modeling: Effects, requirements, and future directions Y. Bouslihim et al. https://doi.org/10.1016/j.sciaf.2025.e02694
- Exploring Hydrological Response to Land Use/Land Cover Change Using the SWAT+ Model in the İznik Lake Watershed, Türkiye A. Tezel et al. https://doi.org/10.3390/w17131924
- Adjusting Bulk Density Observations in the Hungarian Soil Information and Monitoring System Using Pedotransfer Functions S. Sohrab et al. https://doi.org/10.1111/ejss.70245
- Deep exploration of soil temperature and moisture dynamics in Europe from surface to depth in the era of global warming R. Sarli et al. https://doi.org/10.1016/j.geodrs.2026.e01111
- Leveraging soil diversity to mitigate hydrological extremes with nature-based solutions in productive catchments: an application and insights into the way forward B. Guillaume et al. https://doi.org/10.5194/hess-29-4661-2025
- Prediction of the spatial distribution of soil organic carbon content in Central European agriculturally used peatlands: a case study of the Grójec Valley, Central Poland S. Pindral et al. https://doi.org/10.1007/s11368-026-04271-3
- Педотрансферні функції фізичних властивостей ґрунтів: методологічні підходи до розроблення, каталог моделей та схеми локальної валідації О. Бігун https://doi.org/10.31073/acss100-02
- NoahPy: a differentiable Noah land surface model for simulating permafrost thermo-hydrology W. Tian et al. https://doi.org/10.5194/gmd-19-57-2026
- Applicability-aware inference of salinisation-metal risk associations from sparse soil data Q. Ma et al. https://doi.org/10.1016/j.geoderma.2026.118057
Saved (final revised paper)
Latest update: 02 Oct 2026
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.
This research introduces methods and tools for obtaining soil input data in European case...
