Measurement of soil saturated hydraulic conductivity, Ks, is normally affected by flow patterns such as macro pore; however, most current techniques do not differentiate flow types, causing major problems in describing water and chemical flows within the soil matrix. This study compares eight models for scaling Ks and predicted matrix and macro pore Ks, using a database composed of 50 datasets. The database includes data regarding Ks, soil bulk density, particle size distribution, with textures ranging from sandy loam to clay. The results showed that among the models tested, the Saxton and Kozeny Carman models performed best for estimating soil Ks using scaling techniques. In contrast, Campbell and Cosby models were not suitable for similar Ks scaling method. Generally, Saxton, Kozeny Carman, Poulsen Saxton, Vereecken, and the Brakensiek models gave the best estimation of soil Ks. Furthermore, all models had smaller estimation deviations for loam soils than for clay loam soils. The results also showed that a sample with the average characteristics of all samples should be taken as a reference point when scaling Ks is used. Overally, the Saxton and Kozeny Carman models are recommended for scaling Ks. The performance of a simple fractal model was not suitable neither for matrix nor for macro pore hydraulic conductivity. Keywords:

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