Version 1
: Received: 7 November 2023 / Approved: 8 November 2023 / Online: 8 November 2023 (06:43:54 CET)
How to cite:
Ahn, J.; Song, C.G.; Park, S.W. Prediction Equation for Sedimentation Upstream Reservoir of the Weir with Numerical and Experimental Approaches. Preprints2023, 2023110498. https://doi.org/10.20944/preprints202311.0498.v1
Ahn, J.; Song, C.G.; Park, S.W. Prediction Equation for Sedimentation Upstream Reservoir of the Weir with Numerical and Experimental Approaches. Preprints 2023, 2023110498. https://doi.org/10.20944/preprints202311.0498.v1
Ahn, J.; Song, C.G.; Park, S.W. Prediction Equation for Sedimentation Upstream Reservoir of the Weir with Numerical and Experimental Approaches. Preprints2023, 2023110498. https://doi.org/10.20944/preprints202311.0498.v1
APA Style
Ahn, J., Song, C.G., & Park, S.W. (2023). Prediction Equation for Sedimentation Upstream Reservoir of the Weir with Numerical and Experimental Approaches. Preprints. https://doi.org/10.20944/preprints202311.0498.v1
Chicago/Turabian Style
Ahn, J., Chang Geun Song and Sung Won Park. 2023 "Prediction Equation for Sedimentation Upstream Reservoir of the Weir with Numerical and Experimental Approaches" Preprints. https://doi.org/10.20944/preprints202311.0498.v1
Abstract
In this study, a new empirical equation was established to predict the sedimentation volume resulting from the construction of a multipurpose weir or low-head dam. The study employed a one-dimensional numerical model (STAFF) to investigate the key parameters affecting sedimentation volume. Short-term predictions were conducted through laboratory experiments with movable bed, and the results indicated that dimensionless unit stream power and the Shields parameter exhibited the most significant correlation with dimensionless deposition volume. Using a multiple regression approach, an empirical equation was formulated and validated for predicting sedimentation in the upstream reservoir of the weir.
Environmental and Earth Sciences, Water Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
