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Assessment of uncertainties in bed load rate and water surface profile computations
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Date
2023-1-12
Author
Genç, Gizem
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Many processes in water resources engineering are disposed to uncertainty due to the inherent variation of many inputs and parameters in time and place. This study mainly consists of two parts. In the first part, probabilistic variations of bed load rates are examined using Meyer-Peter Müller and Einstein-Brown approaches under the effect of different bed slopes, bed materials, and flow rates in the Miliç Basin. The results of the first part offer an insight into the probabilistic nature of bed resistance. With this awareness, the changes in the water surface profile are analyzed in the second part of the study. The Monte Carlo simulation method is utilized to carry out the uncertainty analysis of bed load rate and water surface profile computations. The recommended Probability Density Function and coefficient of variation for hydraulic variables reported in the literature are designated for the milestone of the simulation. To appraise the outcomes, the Chi-Square and Kolmogorov-Smirnov tests are applied as part of the Goodness of Fit test. Consequently, mainly Beta and Gamma distributions are observed for the bed load transport rate in the study area. As the expanse of the second part, Manning’s roughness coefficient and the flow rate are investigated by integrating Monte Carlo simulation with the HEC-RAS model for Taşlıdere Creek. Consequently, when uncertainty analysis is conducted for flow rate and Manning’s roughness coefficient jointly, mainly Gamma and Log-normal distributions are observed for the bed load transport rate.
Subject Keywords
Uncertainty
,
Bed load rate
,
Monte Carlo simulation
,
Flow depth
,
Manning’s roughness coefficient
URI
https://hdl.handle.net/11511/102014
Collections
Graduate School of Natural and Applied Sciences, Thesis
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G. Genç, “Assessment of uncertainties in bed load rate and water surface profile computations,” M.S. - Master of Science, Middle East Technical University, 2023.