Journal ArticleDOI
A Unifying Quantitative Analysis of Soil Texture
Mostafa A. Shirazi,L. Boersma +1 more
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This article is published in Soil Science Society of America Journal.The article was published on 1984-01-01. It has received 401 citations till now. The article focuses on the topics: Texture (geology) & Soil texture.read more
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Book ChapterDOI
RUSLE: Revised universal soil loss equation
TL;DR: In this paper, many changes for estimating erosion by water in RUSLE, the revised universal soil loss equation, have been proposed, including computerizing the algorithms to assist with the calculations and developing a seasonally variable soil erodibility term (K).
Journal ArticleDOI
Three-parameter lognormal distribution model for soil water retention
Abstract: Many models for soil water retention have been proposed. However, most of these models are curve-fitting equations and do not emphasize the physical significance of their empirical parameters. A new retention model that exhibits increased flexibility was developed by applying three-parameter lognormal distribution laws to the pore radius distribution function ƒ(r) and to the water capacity function, which was taken to be the pore capillary pressure distribution function ƒ(ψ). This model contains three parameters that are closely related to the statistics of ƒ(ψ): the bubbling pressure ψc, the mode ψ0 of ƒ(ψ) and the standard deviation σ of transformed ƒ(ψ). By comparison of this model with three existing models (the van Genuchten model, the Brooks-Corey model, and the modified Tani model), it was shown that ψc, ψ0, and σ are all essential for a general retention model.
Journal ArticleDOI
Event soil loss, runoff and the universal soil loss equation family of models: A review
TL;DR: In this paper, it was shown that using runoff values from cropped areas is necessary to account for differences in infiltration capacities between vegetated and tilled bare fallow areas, but requires re-evaluation of the crop factors.
Journal ArticleDOI
From pedotransfer functions to soil inference systems
TL;DR: The concept of the soil inference systems (SINFERS), where pedotransfer functions are the knowledge rules for inference engines, is proposed, where the first approach to a soil inference system can optimally predict various important physical and chemical properties from the information utilising PTFs as theknowledge rules.
Journal ArticleDOI
Comparison of different approaches to the development of pedotransfer functions for water-retention curves
TL;DR: In this article, both parametric and point estimation PTFs using different approaches: multiple linear regression (MLR), extended nonlinear regression (ENR), and artificial neural network (ANN) are presented for Australian soil.
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