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<p>Regional and national 3D soil hydraulic maps enhance understanding of soil hydraulic properties, essential for environmental assessments. However, data aggregation is often necessary in large-scale models to facilitate the modelling of complex soil characteristics. This study presents a soil hydrologic groups map for Hungary, derived through k-means clustering and expert-based rules. Clustering was applied to the 100 m resolution 3D HU-SoilHydroGrids database, considering eight hydraulic parameters across six depths. The accuracy of these maps is limited for rare soil types with extreme characteristics due to their small spatial extent and sparse representation in national datasets. To account for these underrepresented soil types, we refined each statistics-based cluster using expert-based rules incorporating soil profile depth, genetic type, electrical conductivity, and exchangeable sodium content. The final classification includes 68 soil hydrologic groups, defined by distinct hydraulic properties, such as van Genuchten parameters to describe water retention, and saturated hydraulic conductivity. This national map supports country-wide hydrological modelling, environmental management, and agricultural planning in Hungary by enabling consistent treatment of similar soils.</p>

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National soil hydrologic groups map for environmental applications using data-driven and expert-based methods

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月29日

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  • Brigitta Szabó,
  • Ronald András Kolcsár,
  • János Mészáros,
  • Annamária Laborczi,
  • Katalin Takács,
  • Gábor Szatmári,
  • András Makó,
  • Kálmán Rajkai,
  • Balázs Benyhe,
  • Károly Barta,
  • László Pásztor,
  • Zsófia Bakacsi

摘要

Regional and national 3D soil hydraulic maps enhance understanding of soil hydraulic properties, essential for environmental assessments. However, data aggregation is often necessary in large-scale models to facilitate the modelling of complex soil characteristics. This study presents a soil hydrologic groups map for Hungary, derived through k-means clustering and expert-based rules. Clustering was applied to the 100 m resolution 3D HU-SoilHydroGrids database, considering eight hydraulic parameters across six depths. The accuracy of these maps is limited for rare soil types with extreme characteristics due to their small spatial extent and sparse representation in national datasets. To account for these underrepresented soil types, we refined each statistics-based cluster using expert-based rules incorporating soil profile depth, genetic type, electrical conductivity, and exchangeable sodium content. The final classification includes 68 soil hydrologic groups, defined by distinct hydraulic properties, such as van Genuchten parameters to describe water retention, and saturated hydraulic conductivity. This national map supports country-wide hydrological modelling, environmental management, and agricultural planning in Hungary by enabling consistent treatment of similar soils.