A New Method for Determining the Soil Erodibility Factor Based on Fuzzy Systems

Determination of the soil erodibility factor (K-factor) is a cumbersome and expensive undertaking in the effort to predict the soil loss rates. The percentage of soil particles less than ۰.۱ mm in diameter, the percentage of organic matter, the structural as well as the textural class and permeability are the most important factors constituting the soil erodi-bility factor. Various methods of direct measurement for indirect prediction using models have been introduced so far for the measurement of K- factor. Using the new topics in in-formation technology, in particular the fuzzy system including the Mamdani Inference Engine, Singleton Fuzzyfier and Centriod Defuzzyfier can determine the soil erodibility factor. The K values obtained with this method were compared with those of USLE method. Over ۳۹۴ samples based on the Wischmeier nemograph as a database were in-cluded in this research work by using the fuzzy system. Using some actual data in the fuzzy system and comparing it with the K values attained with the USLE model by calcu-lation of the regression coefficient, the applicability of this system was revealed.

Keywords:

Fuzzy Systems , RUSLE model , Soil erodibility , USLE model