Multivariate geostatistical analysis of soil permeability and spatial variability using deterministic and stochastic approaches
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Abstract
The present research modeled the spatial variability of the apparent permeability of the Chone canton soil, Ecuador, through a combined physical-statistical and geostatistical approach. The study was developed under a quantitative, applied, non-experimental and cross-sectional design, integrating direct measurements of permeability in the field, complementary soil physical variables and spatial interpolation tools in S-GeMS. A total of 64 permeability observations and a spatial mesh of 1600 porosity values were analyzed, obtaining a mean of 17.74, a median of 17.79 and a range between 9.27 and 23.65, while porosity presented a mean of 5.82 and lower relative dispersion. The bivariate analysis showed a moderate positive correlation between permeability and porosity (r = 0.580685), which confirmed the usefulness of the latter as an auxiliary covariate, although insufficient to explain the hydraulic response of the soil on its own. The variographic analysis showed spatial dependence of permeability and moderate anisotropy, indicating that the continuity of flow in the soil changes according to direction and responds to local structural controls. Modelling by kriging and cokriging allowed the generation of continuous surfaces of spatial distribution, identifying sectors with lower hydraulic response and, therefore, greater potential susceptibility to waterlogging or poor drainage. Overall, the findings show that soil permeability in the study area is not a homogeneous or static property, but a spatially structured variable whose geostatistical representation provides key information for local hydrological interpretation and for territorial management of vulnerable areas
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