Predicting the Interactions between Flow, Sediment and Riparian Vegetation

The summary for the Predicting the Interactions between Flow, Sediment and Riparian Vegetation grant is detailed below. This summary states who is eligible for the grant, how much grant money will be awarded, current and past deadlines, Catalog of Federal Domestic Assistance (CFDA) numbers, and a sampling of similar government grants. Verify the accuracy of the data FederalGrants.com provides by visiting the webpage noted in the Link to Full Announcement section or by contacting the appropriate person listed as the Grant Announcement Contact. If any section is incomplete, please visit the website for the Bureau of Reclamation Denver Office, which is the U.S. government agency offering this grant.

Predicting the Interactions between Flow, Sediment and Riparian Vegetation: The strategic challenge for the future is to ensure adequate quantity and quality of water to meet human and ecological needs in the face of growing competition among domestic, industrial/commercial, agricultural and environmental uses. To address water resource problems likely to emerge in the next 10 to 15 years, decision makers at all levels of government will need to make informed choices among often conflicting and uncertain alternative actions. These choices are best made with the full benefit of research and analysis. This project is the result of a collaborative proposal developed by BOR, UNM, DRI and ESI researches to the 2010 Reclamation Science and Technology Program; taking advantage of the complementary capabilities of these researches and institutions. The research will add capacity for modeling the complex interactions between, flow, sediment, and riparian vegetation by building upon the extensive experiences of the research team. This award will provide the University of New Mexico the capability to develop a module of vegetation hydraulics using currently cutting-edge approaches. The study will incorporate influences of stream flow on plant sizes, flexibility and density for integrating UNM algorithms for dynamic hydraulic roughness.