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Title: Sediment yield variability in Spain: a quantitative and semiqualitative analysis using reservoir sedimentation rates
Authors: Verstraeten, Gert ×
Poesen, Jean
de Vente, Joris
Koninckx, X #
Issue Date: Mar-2003
Publisher: Elsevier science bv
Series Title: Geomorphology vol:50 issue:4 pages:327-348
Abstract: An existing dataset of area-specific sediment yield (SSY) for 60 catchments in Spain that was retrieved from sediment deposition rates in reservoirs [Avendano Salas, C., Sanz Montero, E., Rayan, C., Gomez Montana, 1997. Sediment yield at Spanish reservoirs and its relationship with the drainage basin area. In: Proceedings of the 19th Symposium of Large Dams, Florence, 1997. ICOLD (International Committee on Large Dams), pp. 863 - 874] reveals that catchment area alone explains only 17% of the variability in SSY. In this study, an attempt to explain the remaining variability in SSY was made using a quantitative and a semiqualitative approach for 22 catchments. During a field survey, the 22 selected catchments were characterised by topography, vegetation cover, lithology, shape and the presence of gullies in the broad vicinity of the reservoir. This information was used to develop a factorial scoring index model that provides a fairly accurate and reliable prediction of SSY A classical multiple regression model using climatic, topographic and land use properties derived from regional datasets could not explain as much variance as the qualitative index model, nor did it appear to be as reliable. The same conclusion could be drawn when using the CORINE soil erosion risk map of southern Europe. The low prediction capability of the multiple regression models and the CORINE soil erosion risk map could be attributed mainly to the fact that these methods do not incorporate gully erosion and that the land cover data are not a good representation of soil cover. Both variables have been shown to be of great importance during the field surveys. Future assessments of SSY could be quickly and efficiently made using the proposed factorial scoring index model. In comparison with other models, which demand more data, the index model offers an alternative prediction tool. (C) 2002 Elsevier Science B.V All rights reserved.
URI: 
ISSN: 0169-555X
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Division of Geography & Tourism
× corresponding author
# (joint) last author

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