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 |
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