Spatial association among soil hydraulic properties, soil texture, and geoelectrical resistivity

Spatial variability of soil hydraulic properties causes considerable variations in water and solute flow and transport processes. It remains a difficult task to determine and describe the spatial pattern of soil physical properties for modeling landscape-scale vadose zone processes. Strategies that involve measurements of relevant variables and appropriate spatial modeling tools need to be identified for this purpose. The objective of this study was to investigate a nested sampling approach for soil hydraulic properties and associated variables, such as soil texture, in a highly variable soil landscape in northeastern Germany dominated by soils derived from glacial till. Additionally, spatially highly resolved and nondestructive measurements of geoelectrical resistivity were examined for their spatial relation to soil physical and transport properties and their applicability in spatial process models of soil hydraulic property coefficients. Two pedotransfer function (PTF) approaches were applied to gain insight into their capacity to estimate the mean and the spatial variation of soil hydraulic property coefficients, although pedotransfer functions are originally not developed for this purpose. State-space models estimated the spatial process of hydraulic conductivity at a soil water pressure head of -50 cm and the van Genuchten parameter n with relatively narrow confidence bands, whereas for α confidence was larger. Geoelectrical resistivity supported the estimation of the spatial distribution of soil hydraulic property coefficients. Despite the fact that without calibration, pedotransfer variable estimates did not always represent the mean of the respective variable, there was generally little spatial fluctuation reflected. However, considerable horizontal and vertical variability in soil textural properties existed within the investigated landscape. The findings suggest that state-space models incorporating intermittent observations and spatial autocovariance behavior provide more flexibility in the estimation of the spatial process of hydraulic functional coefficients than regression type functions only.