Numerical Modeling of soil-landscape relationships using diversity indices and conditional probability: A case study from an Iranian arid region

Abstract

We quantified some mental and qualitative concepts about the soil-landscape relationships by numerical analysis of landforms in soil identification using diversity indices and conditional probability with a given sample size in Darab and Khosuyeh plains (a rural district) in the south of Iran in Fars province. The geomorphology map was prepared based on the Zinck method and used as a basic design for soil sampling. Finally, 200 soil profiles (0-150 cm) were excavated and described. Diversity indices and conditional probability were calculated based on soil taxonomic and geomorphological hierarchies. The results showed that diversity indices increase from landscape to landform level. The lowest and highest diversity indices were obtained at each geomorphic level for the soil order and soil family. The geomorphic diversity based on the soil taxonomy hierarchy showed that soil orders, including Entisols and Inceptisols, are observed in various landscapes and landforms. In contrast, some soil classes, such as Mollisols and its lower levels (suborder, great group, etc.), did not have geomorphic diversity. The conditional probability based on the geomorphological hierarchy indicated that the presence possibility of specific soil at the higher level (landscape) is less than, the lower level (landform), which indicates the more homogeneity of soils at lower geomorphic levels. However, the probability of observing a certain geoform increased according to the soil classification hierarchy, consistent with the results of diversity indices. The efficiency of diversity indices and conditional probability in showing the distribution and possibility of soil separation depends on the alignment of soil and geomorphological processes and the diagnosis of these processes.