Multi-Algorithm Reservoir Sedimentation Estimation

The summary for the Multi-Algorithm Reservoir Sedimentation Estimation 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, which is the U.S. government agency offering this grant.

Multi-Algorithm Reservoir Sedimentation Estimation: Water resource management in the western U.S. is reliant upon aging reservoirs for critical storage and flood mitigation. One impending concern is the sediment design life of these reservoirs, which remains largely uncertain due to both practical and logistical challenges in sediment monitoring. This work aims to comprehensively estimate historical, current, and projected future sediment loading along with attendant uncertainties through the coordinated application of multiple sediment modeling approaches over the western U.S. This framework will integrate empirical, conceptual, and process‐based models (5 models in total) across key reservoirs using the overarching 1/16° Variable Infiltration Capacity model structure developed for USBR by Livneh et al. (2015). Focus will be given to model uniqueness so as to incorporate and test truly independent sediment model physics. In addition, the importance of model scale will be investigated. Rigorous evaluation of this modeling framework will include calibration and validation of simulated sediment loading and discharge. This framework will be applied to un‐surveyed or not recently surveyed reservoirs and will enable estimates of projected sediment and hence provide a probabilistic estimate of reservoir design life. Major outcomes will be an improved understanding of sedimentation processes and an estimate of uncertainty. Overall, this effort can be used to identify areas of greatest risk for sedimentation and inform mitigation strategies.