Evaluation and Comparison of Grey GM (1,1) and Skaggs Models in Estimating Particle Size Distribution of Soils in the Shahrekord Plain

Document Type : Research Article

Authors

• H. Beigi Harchegani
• Y. Ostovari

10.22067/jsw.v0i0.19234

Abstract

Particle size distribution (PSD) is one of the most important soil physical properties. The Grey Model GM(1,1) is a new method and different from empirical and parametrical models for description and estimation of soil particle size distribution. In this study, the models of Grey GM(1,1) and Skaggs have been used to estimate PSD in five soil textural classes including 138 soil samples taken from Shahrekord Plain. For evaluating and comparison of two models, four statistical indices (MSE, MAPE, AAE, R2) and 1:1 lines were used. The results showed that the performance of both models was relatively good in all five textures. However, Skaggs and Grey GM(1,1) had the best performance in loam and clay textures, respectively. It seems that the performance of Skaggs and Grey GM(1,1) models improved when soil textures changed to coarser and finer textures, respectively. Absolute cumulative error (AAE) of the Skaggs model in some textures tended to decrease while that of the Grey GM(1,1) tended to slightly increase with increasing uniformity and curvature indices of soil.

Keywords

• Grey GM(1
• 1) model
• Skaggs model
• Shahrekord plain
• Particle size distribution

20.1001.1.20084757.1391.26.6.1.3

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