Prediction of Specific Surface area and Cation Exchange Capacity Using Fractal Dimension of Soil Particle Size Distribution

Document Type : Research Paper

Authors

1 Ph.D student of soil science, Tehran University

2 Ph.D student of soil science, Tabriz University

3 Associate professor, Faculty of Agriculture, Guilan university

4 Assistance Professor, Faculty of Agriculture, Guilan university

Abstract

Cation exchange capacity and specific surface area are among some of the important soil characteristics the direct measurement of which is laborious, costly and time consuming. Therefore, fractal dimension of particle size distribution has been widely studied in relation with many such dynamic and static processes as transmission of water and solutes, water holding capacity, heat storage and conductivity, etc., and as a useful parameter, it has been proposed for property estimation as related to soil texture. Throughout the present research, the relationship between fractal dimensions of particle size distributions (Dm) vs. specific surface and cation exchange capacity for 40 soil samples (32 samples for finding the empirical functions and 8 for testing of the derived functions), from Gilevan region, with textures ranging from sandy to clay and different parent materials were evaluated. The obtained results showed that the value of Dm of the soil samples ranged from 2.45 to 2.99; the finer the soil texture, the larger the fractal dimension Dm. The Dm-specific surface area and Dm-cation exchange capacity relationships were described by power functions (R2=0.87 and 0.80, (significant at probability level of 0.01)), respectively. Testing of Dm-clay content, Dm-specific surface area and Dm-cation exchange capacity relationships showed significant correlation (probability level of 0.01) for the measured vs. predicted data. The results indicated that Dm can be used as an integrating index for estimating the specific surface area as well as cation exchange capacity of soils from particle-size distribution, useful in modelings and simulations.

Keywords


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