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publication venue for: Predictability and uncertainty of the soil erodibility factor using a global dataset
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type: Periodical
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Predictability and uncertainty of the soil erodibility factor using a global dataset
page end: 22
type: Thing
type: Article
most specific type: Article
origen: scopus
volume: 31
has publication venue: Catena
type: Information Content Entity
e iscopus: 2-s2.0-0031284762
date time value: article date 594
most specific type: Document
freetext keyword: 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
type: Document
abstract: 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.
type: Generically Dependent Continuant
crisid: 594
type: Continuant
related by: authorship 2795
issue: 1-2
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estado: published
page start: 1
related by: authorship 2794
doi: 10.1016/S0341-8162(97)00036-2
related by: authorship 2796

Generically Dependent Continuant
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RDF description of Predictability and uncertainty of the soil erodibility factor using a global dataset - http://orbis.uaslp.mx/vivo/individual/scopus593
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date: 2026-08-25T13:03:43
publisher: vivo
type: Document

Article
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