Probabilistic Prediction of Riverine Bathymetry
2011
Holland, K T
The goal of this effort is to develop methods for imaging riverine flows that can be applied under operational Naval scenarios to aide in the prediction of relevant riverine conditions (e.g. hydraulic depth, thalweg position, etc.) and that are consistent with related efforts to develop analytic and probabilistic forecasting models for the riverine environment. The objectives of this effort are to develop advanced methods of analysing motion imagery to estimate riverine flows in conjunction with the assessment of existing and newly developed riverine modeling frameworks. These frameworks include a probabilistic system being developed to predict the value and uncertainty of variables that are relevant to riverine operations, such as water depth. As such models are proceeding as related efforts outside the scope of this award, the focus of this work is to assure that the coverages, resolutions, accuracies and overall quality of estimated flow speeds and directions are consistent with use in these frameworks and applicable to operational scenarios. In addition, we seek to compare this optical approach to additional methods of estimating flows such as with GPS-equipped surface drifters or Unmanned Underwater Vehicles (UUV). The focus of the probabilistic design is to rigorously incorporate uncertainty in natural river conditions relating to river width, surface flow speeds, discharge ranges, and/or river path into an operational decision aide for estimating river depths.
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Эту запись предоставил AVANO
