Publication Details |
Category | Text Publication |
Reference Category | Journals |
DOI | 10.1016/j.jhydrol.2009.01.033 |
Title (Primary) | A principal component regression approach to simulate the bed-evolution of reservoirs |
Author | Gurmessa, T.K.; Bárdossy, A. |
Source Titel | Journal of Hydrology |
Year | 2009 |
Department | ASAM |
Volume | 368 |
Issue | 1-4 |
Page From | 30 |
Page To | 41 |
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. |
Persistent UFZ Identifier | https://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 10.1016/j.jhydrol.2009.01.033 |