- Reclamation
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- Monitoring of the Lake Powell Delta
Monitoring of the Lake Powell Delta
Project ID: 6847
Principal Investigator: Blair Greimann
Research Topic: Sediment Management and River Restoration
Funded Fiscal Years:
2006
Keywords: None
Research Question
* What are the magnitudes and rates of incision, bank erosion, slope failures, and delta consolidation in the Lake Powell Delta?
Need and Benefit
With a volume of approximately one million acre-feet (AF), the Lake Powell deta is perhaps the largest sediment delta in any Reclamation reservoir. The lowering of Lake Powell has produced an unprecedented opportunity to study delta processes. The lowering of the reservoir has caused several processes to occur:
* Incision: the drop in water surface elevation causes a channel to form through the sediment deposits.
* Bank erosion: the steep banks caused by the incision are gradually eroded by the flowing water.
* Slope failure: the ground water gradient towards the incising channel causes multiple slope failures throughout the delta.
* Delta consolidation: the release of pore water causes the sediments in the delta to consolidate.
This Science and Technology (S&T) Program research project will collect data to quantify the magnitude and rate of these processes. The data could be used to validate numerical models of these processes and more importantly to further our understanding and predictive capability of these processes. Improving our predictive capability of these processes would improve our ability to manage sediment in our reservoirs. For example, sluicing sediment through reservoirs is sometimes necessary to increase the lifespan of a reservoir or to maintain optimal functionality of the reservoir. To sluice sediment, a prediction of the amount of water required and the amount of sediment removed is necessary. The prediction requires quantification of the above processes. As another example, sediment management during dam removal requires a prediction of the same processes.
Currently, there is a lack of quantitative data of these processes at large scales. The main problem in developing better predictive models of these processes is sufficient data to verify these models.
Contributing Partners
Contact the Principal Investigator for information about partners.
Research Products
Please contact research@usbr.gov about research products related to this project.
