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PORTAIL D'INFORMATION GÉOGRAPHIQUE

Artificial neural networks of soil erosion and runoff prediction at the plot scale

Auteur :
LICZNAR, P.

Description :
The aim of this study was to investigate the applicability of using neural networks to quantitatively predict soil loss from natural runoff plots. Data from 2879 erosion events from 8 locations in the United States were used. The AA. present a comparison study between results from erosion and runoff procedures of the WEPP technology (Water Erosion Prediction Project model) and from artificial neural networks. In most cases, the results received from the neural networks were better than those from WEPP, although the neural networks generally tended to under-predict runoff and soil loss values.


Type de document :
Article de périodique

Source :
Catena (Giessen), issn : 0341-8162, 2003, vol. 51, n°. 2, p. 89-114, nombre de pages : 26, Collation : Illustration, Références bibliographiques : 22 ref.

Date :
2003

Editeur :
Pays édition : Allemagne, Cremlingen-Destedt, Catena

Langue :
Anglais
Droits :
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