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- Quantification of accuracy improvements related to multibeam data processing.
Quantification of accuracy improvements related to multibeam data processing.
Project ID: 23025
Principal Investigator: David Varyu
Research Topic: Sediment Management and River Restoration
Funded Fiscal Years:
2023 and
2024
Keywords: None
Research Question
What is the minimum level of processing required (using industry standard software) that provides accurate area-capacity curves? The null hypothesis is that a complete, fully detailed processing of all sweeps and profiles is required to develop accurate area-capacity curves. The alternate hypothesis is that there is a level of processing earlier in the sequence of processing steps where diminishing returns are achieved. That is, running the correct combination of filters will provide an accurate surface from which Area-Capacity curves are developed, without needing to execute the time-consuming, manual processing that is currently employed for reservoir surveys. Two reservoirs have been surveyed in FY2022, Santa Cruz Reservoir in New Mexico and McGee Creek Reservoir in Oklahoma. These surveys were conducted at the cost of different clients, and project deliverables for these efforts include an area-capacity table.
Need and Benefit
A forthcoming D&S will require Reclamation's Regional Offices to develop sediment management plans at Reclamation reservoirs, which will undoubtedly increase the number of bathymetric surveys conducted at Reclamation facilities. The increase in data collection efforts will necessitate a means of providing accurate and reliable area-capacity curves in a more efficient manner than is currently employed. If this project is not funded, the cost of processing multibeam data will likely be twice as much as is necessary.
It is hypothesized that processing time of multibeam data can be reduced by half. This reduction will not impact data collection time, the time necessary to generate reports and other project deliverables, or project management time. However, processing time is currently budgeted and expended as twice the data collection time (sometimes more in practice), and data processing is, typically 15% of the total project cost. Depending on reservoir size, this can be $5,000 to $25,000. The hypothesized savings for a given reservoir could range from $2,500 to $12,500 and average $7,500 per project. Our group typically conducts 5 bathymetric surveys per year. Even without the anticipated increase in workload related to the upcoming D&S, improved processing techniques will save an average of $37,500 annually on data processing. The investment in this research, ~$50,000, will be paid back in processing savings in less than two years.
Contributing Partners
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Research Products
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