Le Roux, JayMararakanye, NdifelaniVan der Laan, MichaelMudaly, LeushanthaWeepener, Harold LouwVan Tol, Johan2026-01-222026-01-222025-06Le Roux, J., Mararakanye, N., Van der Laan, M. et al. 2025, 'South African soil, land cover and weather generator file databases for SWAT applications', Journal of Hydrology : Regional Studies, vol. 59, art. 102387, pp. 1-15. https://doi.org/10.1016/j.ejrh.2025.102387.2214-5818 (online)10.1016/j.ejrh.2025.102387http://hdl.handle.net/2263/107465APPENDIX A. Metadata for SWAT Baseline Data. APPENDIX B. List of land cover types in the SWAT database (excluding parameters) that was linked to the National Land Cover (2014, 2018 and 2020) maps of SA.DATA AVAILABILITY : I have shared the link where data is available South African soil, land cover and weather generator file databases for SWAT(Mendeley Data).STUDY REGION : South Africa. STUDY FOCUS : The focus of the study is to develop soil, land cover and weather generator file datasets for Soil and Water Assessment Tool (SWAT) applications in South Africa. The first objective was to format national datasets for use as baseline to run the SWAT model in South Africa. The second objective was to evaluate the performance of the baseline input data by applying the national datasets in four (previously simulated) research catchments. NEW HYDROLOGICAL INSIGHTS FOR THE REGION : The input datasets comprise of geo-spatial datasets at a national scale to run ArcSWAT or QSWAT (graphical user interface for SWAT in ArcGIS and SWAT+ in QGIS, respectively) in South Africa including: SWAT catchment outline data (tertiary and quaternary); Land cover maps at 20–30 m resolution including South African National Land Cover (2014, 2018, 2020) linked to SWAT land cover codes; A soil map with SWAT attribute data derived from pedotransfer functions of the Land Type Database of South Africa useable at a scale of 1:250,000; Weather statistics (WGN) files for 12 weather stations obtained from the Agricultural Research Council in South Africa. The national baseline data is an important step forward in hydrological modelling by assisting modellers to set-up and run the SWAT model in South Africa.en© 2025 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).QSWATArcSWATInput datasetsBig dataData evaluationSouth Africa (SA)Soil and water assessment tool (SWAT)Article