Long-time 3D CFD modeling of sedimentation with dredging in a hydropower reservoir
- 108 Downloads
The purpose of the current study was to present a 3D computational fluid dynamics (CFD) model that can be used to predict long-term (11 years) bed changes in a reservoir due to sedimentation and dredging and that can be done with a reasonable computational time (18 h) on a desktop computer.
Materials and methods
The numerical model solved the Navier-Stokes equations on a 3D non-orthogonal unstructured grid to find the water velocities and turbulence. The convection-diffusion equation for suspended sediment transport was solved to find the sediment deposition pattern. Bed changes were computed and used to adjust the grid over time. Thereby, bed elevations over time were computed. The effect of dredging was also included in the model, and how this affected the bed elevation changes. The main feature of the numerical model enabling a reasonable computational time was implicit numerical methods giving the possibility to use long time steps.
Results and discussion
The results were compared with annually measured bed elevation changes in the reservoir over 11 years. This gave 11 figures of bed elevation changes, due to the combined effect of sedimentation and dredging. Comparing the annually computed and measured bed changes, there was a fair agreement for most of the years. The main deposition patterns were reproduced. The amount of sediments removed in three dredging campaigns were also computed numerically and compared with the measured values. Parameter tests were done for the grid size, fall velocity of the sediments, cohesion, and sediment transport formula. The deviation between computed and measured dredged sediment volumes was less than 16% for all these four parameters/formulas.
The 3D CFD numerical model was able to compute water flow, sediment transport, and bed elevation changes in a hydropower reservoir over a time period of 11 years. Field measurements showed reasonable agreement with the computed bed elevation changes. The results were most sensitive to the sediment particle fall velocity and cohesion of the bed material.
KeywordsBed level changes Dredging Navier-Stokes equations Numerical modeling Reservoir Sediment transport
The authors would like to thank the German Waterways and Shipping Administration for providing the data for the current study.
- Astor B, Gehres N, Hillebrand G (2014) From source to mouth, a sediment budget of the Rhine river: grain size distribution of suspended sediment samples in the Rhine and its tributaries. BfG 1798. Bundesanstalt für Gewässerkunde, Koblenz (in German)Google Scholar
- Banhold K, Frings R, Schüttrumpf H (2017) Sediment budget of the High Rhine and Upper Rhine from Konstanz to Iffezheim. In: Hillebrand G, Frings RM (eds) From source to mouth, the sediment budget of the Rhine river for the period 1991–2010. Report KHR/CHR II-22. International Commission for the Hydrology of the Rhine basin, Lelystad. pp 42–47, ISBN: 978-90-70980-39-9, DOI: https://doi.org/10.5675/KHR_22.2017 (in German)
- Engelund F, Hansen E (1967) A monograph on sediment transport in alluvial streams. Teknisk Forlag, CopenhagenGoogle Scholar
- Hillebrand G (2014) Sediment analysis of drill core samples from the IKSR investigation of the reservoirs in the Upper Rhine from the years 2000 to 2002. KLIWAS-Report series, KLIWAS-56/2014, pp. 63. Federal Institute of Hydrology, Koblenz (in German)Google Scholar
- Hillebrand G, Otto W, Vollmer S (2012) Findings from ADCP-measured flow velocities and suspended sediment concentrations at the Upper Rhine. 2nd IAHR Europe Conference, Munich, GermanyGoogle Scholar
- Hillebrand, G, Otto, W, Schmegg, J, Vollmer, S, Gehres, N (2015) Upgrading the suspended sediment measurement network of the German Waterways and Shipping Administration. BfG-Report Nr. 1799, Federal Institute of Hydrology, Koblenz (in German)Google Scholar
- Mahmood K (1987) Reservoir sedimentation: impact, extent and mitigation. World Bank Technical Paper 71, Washington, DCGoogle Scholar
- Mirbach S, Lang U (2017) Density-driven underflows with suspended solids in Lake Constance. J Soils Sediments. https://doi.org/10.1007/s11368-017-1753-x
- Noack M, Hillebrand G, Seidenkranz U, Wieprecht S (2016) Investigation of erosion stability of cohesive sediment deposition in the spillway channel of the Iffezheim barrage at the Rhine river. Hydrol Wasserbewirtsch 60(3):164–175 (in German)Google Scholar
- Ruether N, Singh JM, Olsen NRB, Atkinson E (2005) Three-dimensional modelling of sediment transport at water intakes. Proceedings of the Institution of Civil Engineers, UK. Water Manag 158:1–7Google Scholar
- Schlichting H (1979) Boundary layer theory. McGraw-Hill Book Company, New York ISBN 978-3-662-52919-5Google Scholar
- Shields A (1936) Use of dimensional analysis and turbulence research for sediment transport, Preussen Research Laboratory for Water and Marine Constructions, publication no. 26, Berlin (in German)Google Scholar
- Winterwerp JC, van Kesteren WGM (2004) Introduction to the physics of cohesive sediment in the marine environment. Elsevier, ISBN 978-0-444-51553-7Google Scholar
- Zanke U (1977) Computation of fall velocities for sediments, Mitteilungen des Franzius-Instituts für Wasserbau und Küsteningenieurwesen der TU Hannover, Vol. 46 (in German)Google Scholar
- Zhang Q, Hillebrand G, Hoffmann T, Hinkelmann R (2017) Estimating long-term evolution of fine sediment budget in the Iffezheim reservoir using a simplified method based on classification of boundary conditions, Geophysical Research Abstracts. Vol. 19, EGU2017-9039, EGU General Assembly 2017Google Scholar