A study on uncertainty-based flood analysis

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MustafaBerkayAKPINAR_MSc_Thesis.pdf

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2023-1

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Akpınar, Mustafa Berkay

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A hydraulic model is a collection of mathematical equations that give a simple representation of reality with the inputs obtained from hydrological assessments to estimate flow, flow depth and velocity in channels. Basically, hydraulic models require digital elevation models, Intensity-Duration-Frequency curves, maximum flows from hydrographs, and roughness coefficients from field studies and/or satellite images. Inherently, these major inputs have uncertainties due to the complex nature of the evaluation processes of inputs and boundary conditions. In recent years, researches have shown that roughness coefficients and evaluated maximum flows may have error margins of 5% to 15%; this may result in underestimation for expected flow depths compared to evaluated ones. In this study, convenient probability distributions in the nature of uncertainties in peak discharge of the input hydrograph and Manning’s roughness value have been investigated separately and in combined manner in flood modelling. The study was conducted and modelled with an automated Monte Carlo-based method of HEC-RAS and Visual Basic Applications software in the catchment of Yılanlı Dere, in Samsun. 1-D hydraulic model was used. The results show that the maximum flows and roughness values may cause uncertainties in flow depths up to 10% of the total capacity of cros-sections without overflow in this region. Moreover, distances of the cross-sections to the hydraulic structures existing along the river and topographic conditions can also directly affect these uncertainties. It is obtained that the distributions of the flow depth at the cross-sections were changed.

Subject Keywords

Hydraulic Models, Uncertainties, Probabilistic Flood Modelling

URI

https://hdl.handle.net/11511/102103

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Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

M. B. Akpınar, “A study on uncertainty-based flood analysis,” M.S. - Master of Science, Middle East Technical University, 2023.