Porous Soil Structure as Heterogeneous Complex Networks

In this paper we present a complex network model based on a heterogeneous preferential attachment scheme as a new way to quantify the porous structure of soils and to relate them with soil texture. We consider the pores as nodes, the properties of which, such as position and size, are described by fixed states in a metric space. An affinity function is introduced to bias the attachment probabilities of links according to these properties. We perform an analytical study of the degree distributions in the model and develop a numerical analysis of the degree distributions in the model for a combination of parameters corresponding to eleven empirical soil samples with different physical properties and five different textures