Publication Details

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Title (Primary) A principal component regression approach to simulate the bed-evolution of reservoirs
Author Gurmessa, T.K.; Bárdossy, A.;
Journal Journal of Hydrology
Year 2009
Department ASAM;
Volume 368
Issue 1-4
Language englisch;
Keywords Reservoir sedimentation; Spatio-temporal bed-evolution; Numerical simulation; Multivariate regression; Principal components regression
Abstract Long-term simulation of reservoir sedimentation suffers from process complexity, lack of data, as well as high computational cost. This work presents an efficient data-driven modeling approach to simulate the spatio-temporal dynamics of bed-evolution reservoirs using principal components regression. The daily bed-evolution of a validated numerical model was used as an input. The first four principal components contributed to some 90% of the total variance of bed-evolution. Multiple linear regression between the eigenvectors of the first four principal components with the inflow discharge, suspended sediment concentration, and differential discharge was able to reconstruct the spatio-temporal bed-evolution. Predictions with similar initial morphological condition performed reasonably. The work is a step forward to advance the assimilation of numerical and data-driven approaches in modeling long-term sedimentation of reservoirs.
ID 216
Persistent UFZ Identifier http://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=216
Gurmessa, T.K., Bárdossy, A. (2009):
A principal component regression approach to simulate the bed-evolution of reservoirs
J. Hydrol. 368 (1-4), 30 - 41