Improving predictions of scour in the vicinity of vegetation in habitat rehabilitation areas

Project ID: 19290
Principal Investigator: Daniel Dombroski
Research Topic: Water Operation Models and Decision Support Systems
Funded Fiscal Years: 2019 and 2020
Keywords: None

Research Question

How can ecohydraulic modeling capabilities be improved by enhancing capability to predict scour in support of habitat and riparian rehabilitation projects?

Need and Benefit

Multi-dimensional hydraulic, sediment, and habitat modeling are now routinely requested by project offices in order to
meet demands for quantitative evaluation of alternative restoration designs. The complexity of ecohydraulic
processes requires improvements in ability to predict interactions that effect localized patterns. Ability to better predict
scour that will affect vegetation recruitment and removal, to the benefit or detriment of habitat rehabilitation projects, is
vitally important to guide designers in order to ensure long-term success. The benefit of the project will be in
producing a more useful tool for restoration practitioners to use in evaluating alternative designs. Given the overall
cost of large-scale restoration projects, the increasing role ecohydraulic modeling is playing in these projects, and the
implications of success or failure of revegetation (or devegetation) actions, Reclamation's involvement in habitat
restoration will benefit from improved capabilities. Reclamation sits at the forefront of many large-scale hydraulic,
sediment, and habitat studies of river and reservoir environments throughout the Western States. As certain types of
analyses become standard practice among these projects, Reclamation has a responsibility to operate efficiently and
effectively. Without continued efforts to improve capabilities, Reclamation's effectiveness in conducting project work
will be limited.

Contributing Partners

Contact the Principal Investigator for information about partners.

Research Products

Please contact research@usbr.gov about research products related to this project.


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Last Updated: 6/22/20