Multi-Algorithm Reservoir Sedimentation Estimation

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Funding Opportunity ID: 293485
Opportunity Number: BOR-DO-17-N027
Opportunity Title: Multi-Algorithm Reservoir Sedimentation Estimation
Opportunity Category: Discretionary
Opportunity Category Explanation:
Funding Instrument Type: Cooperative Agreement
Category of Funding Activity: Science and Technology and other Research and Development
Category Explanation:
CFDA Number(s): 15.560
Eligible Applicants: Public and State controlled institutions of higher education
Additional Information on Eligibility:
Agency Code: DOI-BOR
Agency Name: Department of the Interior
Bureau of Reclamation
Posted Date: Apr 27, 2017
Close Date: May 11, 2017
Last Updated Date: Apr 27, 2017
Award Ceiling: $298,515
Award Floor: $298,515
Estimated Total Program Funding: $298,515
Expected Number of Awards: 1
Description: 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.
Version: Synopsis 1





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