A New Innovative Approach with Revised Pythagorean Fuzzy SWARA in Assessing of Soil Erodibility Factor

Year 2025, Volume: 31 Issue: 1, 182 - 195, 14.01.2025

Aykut Çağlar , Barış Özkan , Orhan Dengiz

Abstract

Soil erosion is a significant issue that threatens to soil in land degradation processes. The soil erodibility factor is a crucial tool for assessing the susceptibility of soils to erosion. The main aim of this study was to compare the results obtained using the Pythagorean Fuzzy-SWARA method which evaluates the impact weights of the criteria considered for the soil erodibility factor of the soils in the micro-basins located in the district of Çarşamba district of Samsun province, with the results obtained using the formula developed by Wischmeier and Smith. To achieve this case, 78 surface soil samples were collected from micro basins and analyzed for organic matter, clay, sand, silt, very fine sand, degree of structure, and hydraulic conductivity parameters. The erodibility factor was then calculated using these data, and spatial distribution maps were created for both methods. In this study, a revised of the Pythagorean Fuzzy-SWARA approach is proposed to calculate the weight values of the criteria. The values were 0.418 for organic matter, 0.227 for clay, 0.120 for degree of structure, 0.100 for hydraulic conductivity, 0.058 for sand, 0.053 for silt, and 0.039 for very fine sand. Soil erodibility values were determined using a linear combination approach, which normalized all parameter values by a standard scoring function. In estimating soil erodibility, our revised Pythagorean Fuzzy-SWARA approach was found to have a significant relationship with the soil erodibility factor method (R2 = 0.691 at the 1% level) compared to the soil erodibility factor method in estimating soil erodibility. Consequently, the method developed here suggests that fuzzy multi-criteria decision-making methods can be an alternative approach for determining the soil erodibility factor.

Keywords

Soil erodibility, Pythagorean Fuzzy Sets, SWARA, RUSLE-K

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