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Predictability and uncertainty of the soil erodibility factor using a global dataset
Erosion prediction; Erosion uncertainty; Fuzzy erodibility; Fuzzy logic; Revised universal soil loss equation; Soil erodibility; Water erosion dataset; erosion prediction; organic matter content; RUSLE; soil erodibility; USLE; water erosion
This paper investigates the predictability of the soil erodibility factor (K) in the revised universal soil loss equation from soil clay content (C), the Naperian logarithm of the geometric mean particle size (D(G)) and organic matter content (OM), using a global dataset compiled from published studies. A multiple regression equation accounted for only 41%25 of the observed variance. Because of the large unexplained variance, an alternative procedure was explored to describe the K data in terms of the lower and upper bounds of the range of variation and the most probable value in this range. However, this approach did not provide sufficient information about the distribution of the observed K values. A procedure based on fuzzy logic and fuzzy mathematical theories was then developed, using the program FUZKBAS, which describes the frequency distribution of observed K values for a given soil, characterised by D(G), C and OM, in terms of membership functions.
Generically Dependent Continuant
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