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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | Washington State University |
| Country | United States |
| Start Date | Oct 01, 2024 |
| End Date | Sep 30, 2027 |
| Duration | 1,094 days |
| Number of Grantees | 3 |
| Roles | Principal Investigator; Co-Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2427354 |
Hundreds of millions of dollars are spent annually to restore stream ecosystems in the United States. One common approach uses beaver mimicry (installing structures akin to beaver dams) to mitigate climate and land-use impacts on river ecosystems. Yet, there is limited scientific understanding of their effectiveness.
That is, do they produce the intended hydrological goals of the restoration? This project will develop the scientific foundation to measure and model the impact of beaver dam analogs on water flows and work with restoration practitioners to learn and monitor restoration effectiveness. The research will provide the hydrologic understanding needed to evaluate, improve, and expand restoration practice.
The fundamental scientific pursuit of this project is to understand how beaver dam analogs influence water yield and streamflow timing by the physical alteration of hydrologic flows among stream-atmosphere-aquifer reservoirs. The project will connect and coordinate the growing scientific understanding of the hydrological impact of common river restoration practices.
Numerical simulations will be used to test the magnitude of storage and release of water produced by restoration actions over a range of climate, soil, geomorphic and design conditions in western North America. The approach includes on-site measurements to test model simulations and evaluate intended restoration outcomes. The project team will co-implement do-it-yourself water/weather measurement stations with local restoration practitioners to develop the needed technical protocols (study design, sensors, and data infrastructure).
The team will engage with resource agency scientists during the data collection, analysis and modeling to improve practitioner-led environmental monitoring and increase the likelihood of restoration success.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Washington State University
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