Applicability of fuzzy and fuzzy analytic hierarchy process methods to determine the optimum soil depth in land suitability evaluation for irrigated rice

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Abstract

The conventional Boolean logic models of land suitability assessment disregard the continuity concepts of the soil and landscape which might cause inaccurate evaluation and classification. To overcome this uncertainty and consequent constraints, the fuzzy set theories were introduced. Therefore, the current study was undertaken to estimate the optimum soil depth that is used in land suitability evaluation for irrigated rice through the fuzzy sets theory and analytic hierarchy process (fuzzy AHP) in Guilan Province, Iran. The square root and quantitative land suitability evaluation methods were employed to calculate traditional land suitability indices (for depths 0–25, 0–50, 0–75, and 0–100 cm). Also, fuzzy and fuzzy AHP methods were used to explore new land indices. The Sarma similarity indices were used to compare the results of traditional and fuzzy methods for different soil depths. The results showed that the compatibility percentage between the representative pedons (0–100 cm) and the findings of this research (0–50 and 0–75 cm) was remarkable. Furthermore, the highest compatibility percentage of land suitability class was related to the comparison of these two former depths and 0 to 100 cm depths in each of the two used fuzzy methods. Besides, except for 0–25 cm depths, actual yield revealed a significant and positive correlation with the rest three soil pedon depths. These findings show that considering 0 to 50 cm soil depth might be a relevant alternative as the optimal depth to evaluate land suitability for rice in paddy fields in Guilan rice-growing area.

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Mahabadi, N. Y., & Soltani, S. M. (2021). Applicability of fuzzy and fuzzy analytic hierarchy process methods to determine the optimum soil depth in land suitability evaluation for irrigated rice. Polish Journal of Soil Science, 54(1), 103–122. https://doi.org/10.17951/pjss.2021.54.1.103-122

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