Predicting Vertical and Lateral Sediment Erosion in River and Reservoir Settings
Project ID: 7356
Principal Investigator: Jennifer Bountry
Research Topic: Sediment Management and River Restoration
Priority Area Assignments: 2012 (Climate Adaptation)
Funded Fiscal Years: 2012, 2013 and 2014
Keywords: sediment, erosion, numerical model, predictions
We propose to address the following two research questions:
1) Is SRH-2D, a current state-of-the-art multidimensional sediment and morphological model, capable of predicting both vertical and lateral sediment erosion and deposition processes?
2) How does the rate of reservoir lowering affect the erosion and redistribution of a large reservoir sediment delta?
Need and Benefit
Numerical sediment transport models have existed for a few decades and can predict the bed elevation changes of a river channel or reservoir delta. However, accurate prediction of the lateral changes, induced by streambank erosion, has been elusive. There are many streams that are neither aggrading nor degrading, but there is considerable lateral migration of the channel through streambank erosion. The deposition and erosion of reservoir deltas is also driven by lateral processes.
Reservoir delta development and river channel morphological development have long been studied qualitatively due to the complexity of physical processes involved. For some projects, such a qualitative approach is adequate; for others, a more accurate quantitative prediction is needed.
For example, on the Savage Rapids Dam project, a multimillion dollar pumping plant was designed by the Bureau of Reclamation (Reclamation) and constructed prior to dam removal. Prediction of sediment impacts associated with dam removal and the upstream watershed was inherent to design parameters of the pump intake, which was placed in the direct path of river sediment downstream of the former dam. However, limitations associated with existing one-dimensional sediment transport models and lack of sediment releases with similar size and at-risk infrastructure introduced uncertainty in predictive capability.
With the recent advancement of physically based multidimensional numerical tools, a relatively reliable, quantitative prediction of channel morphological change has become feasible in recent years. Over the past 10 years, Reclamation has been actively involved in the research and development of such models such as SRH-2D. Despite that SRH-2D has been used in a few projects to predict dam removal sedimentation processes such as on the Klamath River, the Colorado River in the reservoir pool behind Palo Verde Dam, and a sediment plug on the Rio Grande, the model accuracy is yet to be demonstrated against independent data. With the large amount of physical model and field data available from the Elwha project, we are in a unique position to test and verify the Reclamation model. Once validated, the model can be used to predict future morphological changes of the river both upstream and downstream of Reclamation dams.
Contact the Principal Investigator for information about partners.
Independent Peer Review
The following documents were reviewed by qualified Bureau of Reclamation employees. The findings were determined to be achieved using valid means.
Comparative Modeling Studies of Reservoir Drawdown Induced Erosion Comparative Modeling Studies of Reservoir Drawdown Induced ErosionComparative Modeling Studies of Reservoir Drawdown Induced ErosionComparative Modeling Studies of Reservoir Drawdown Induc (interim, PDF, 4.1MB)
By Dr. Jennifer Duane
Report completed on October 24, 2014
Bureau of Reclamation Review
The following documents were reviewed by experts in fields relating to this project's study and findings. The results were determined to be achieved using valid means.
Predicting Erosion in Rivers and Reservoir Settings (final, PDF, 939KB)
By Yong Lai
Publication completed on September 30, 2014
Modeling of Delta Erosion during (interim, PDF, 1.6MB)
By Dr. Yong Lai
Report completed on October 27, 2014
Modeling Delta Erosion with a Landscape Evolution Model (final, PDF, 1.0MB)
By Nathan Bradley
Report completed on October 27, 2014