Aggregating 3D soil hydraulic properties for large-scale environmental modelling

Understanding soil water management properties is crucial for agricultural, hydrological, and environmental modelling. To enhance the description of soil hydraulic processes, we developed national 3D soil hydraulic maps for Hungary at 100 m resolution, covering six soil layers down to 2 m depth (HU-SoilHydroGrids). This dataset includes continuous values of calculated soil hydraulic parameters, but aggregating this information is necessary to facilitate its use in national large-scale hydrological models with significant computational demands.

In Hungary, the methodology of the Várallyay soil water management categories map has been used for the hydrological classification of soils before the availability of HU-SoilHydroGrids. This nationwide map supports agricultural water management planning and includes nine soil water management categories and seventeen variants, established through expert rules based on field capacity, wilting point, available water content, infiltration rate, saturated hydraulic conductivity, and soil texture variations.

The newly available HU-SoilHydroGrids maps allow statistically based classification of soil hydraulic properties. In our study, we classified Hungarian soils using both national and international studies. Our methodology began with clustering via the k-means method on the HU-SoilHydroGrids database, considering eight soil hydraulic parameters across six soil depths, including van Genuchten parameters, water content at saturation, field capacity, wilting point, available water content, and hydraulic conductivity. This analysis identified twelve statistically distinct soil classes.

To ensure the inclusion of underrepresented soil groups with significant differences in water management, we refined these clusters with expert-based rules. Consequently, we further subdivided the twelve groups by soil profile depth, genetic soil type, electrical conductivity, and exchangeable sodium content. Combining statistical methods with expert-based rules, we established 68 categories. These soil hydrological groups provide a possible solution to aggregate the soil hydraulic data in environmental modelling applications.

The preparation of the HU-SoilHydroGrids dataset was carried out within the framework of the Széchenyi Plan Plus program with the support of the RRF 2.3.1 21 2022 00008 project. The derivation of the soil hydrological groups was funded by the Sustainable Development and Technologies National Programme of the Hungarian Academy of Sciences (FFT NP FTA). The statistical computations were performed in the HUN-REN Cloud (https://science-cloud.hu/) e-infrastructure.