Combination of Fuzzy Logic and Analytical Hierarchy Process Techniques to Assess Potassium Saturation Percentage of Some Calcareous Soils (Case Study: Fars Province, Southern Iran)

Abstract

This research was carried out to evaluate the capability of a combined fuzzy logic-based approach and analytical hierarchy process (AHP) for potassium saturation percentage (KSP) estimation in some calcareous soils of southern Iran. Based on a reconnaissance soil survey, 52 soil series were selected and different physical and chemical properties were determined. Five soil parameters including clay, cation exchange capacity, calcium carbonate equivalent, electrical conductivity, and organic carbon were chosen for analysis. Mapping was developed with the kriging method for each parameter. Different fuzzy membership functions were employed and weights for all parameters were calculated according to AHP. Finally, KSP classes were provided for each land unit. Results indicated that about 60% of the studied area is classified as having moderate to high KSP content (>3%) and 40% of had low or very low KSP content (<3%). Then 15 sample points were used for determination of the accuracy of the fuzzy method. Results showed that the fuzzy and AHP methods have a high accuracy for KSP estimation in the studied soils. Further development of the fuzzy and AHP methods would be worthwhile for improving the accuracy of KSP analysis.

Keywords

• potassium saturation percentage (KSP)
• calcareous soils
• GIS
• fuzzy
• analytical hierarchy process (AHP)