Estimating the Scaling Parameter of Arya - Paris Model by Various Methods to Improve Estimation of Soil Moisture Characteristic Curve

Document Type : Research Paper

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Abstract

          Direct measurement of soil moisture curve (SMC) is time consuming, difficult and costly in laboratory. Therefore, many attempts have been made to predict SMC from soil physical and chemical properties indirectly. Arya - Paris model predicts SMC from soil particle size distribution data. The model estimates pore radius from the radius of spherical particles using a scaling parameter (α). The objective of this study was to evaluate estimation of α by six different methods to improve the predicted SMC from Arya - Paris model. Comparisons made on 14 soil samples with different textures collected from the eastern region of the Guilan province showed that the estimated SMC with different α produced different accuracy. It was highly depended on the selected parameter. In other words the method of determining α played a key role in the accuracy of SMC prediction. The results showed that linear α as described by Arya et al. and constant α of 1.38 as recommended by Arya - Paris were the best scaling parameters for estimation of SMC.

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References

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Water and Soil Science
Volume 21, Issue 3 - Serial Number 3
November 2011
Pages 103-114

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