Discharge and water level uncertainty in bifurcating rivers

Matthijs R.A. Gensen

Research output: ThesisPhD Thesis - Research UT, graduation UT

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Abstract

Accurate predictions of water levels, discharges and their uncertainties are essential for flood risk management of rivers. In river deltas, the river often splits into multiple branches. The discharge of the upstream river is distributed over the branches at the bifurcations. This discharge distribution is controlled by the discharge capacity of the downstream branches. This capacity is mainly determined by the hydraulic roughness and geometry of the branch and it varies with the water level, giving rise to a feedback mechanism between water levels and discharge distribution. Therefore, the uncertainty in discharge distribution is one of the main drivers of water level uncertainty and associated flood risk.
In previous studies, the water level uncertainty has been quantified for single-branch rivers. The aim of this thesis is to quantify water level uncertainties in a bifurcating river system. This is achieved by both hydraulic modelling and by data analysis. The bifurcating Rhine river in the Netherlands is used as a case study.
The thesis shows that the feedback mechanism at the bifurcation balances out water level variations between the branches. Such variations may originate from uncertainties in hydraulic roughness of the river bed or from changes in the geometry through human intervention. The largest of the downstream branches dominates the uncertainty in discharge distribution and water levels throughout the entire river system.
The thesis thus concludes that the physics of a bifurcation significantly affect system-wide water levels and water level uncertainties, and therefore need to be accounted for to accurately estimate the uncertainties in water levels and discharges. It is therefore recommended to consider these physics in flood risk analyses. Observations of discharges and water levels are required for accurate hydraulic modelling and for data analysis, but errors in such observations may limit the accuracy of the hydraulic models and of the data analysis. Recommendations are done for approaches in which hydraulic models and data analysis are explicitly combined to potentially further increase the accuracy of water level predictions.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • University of Twente
Supervisors/Advisors
  • Hulscher, Suzanne J.M.H., Supervisor
  • Warmink, Jord Jurriaan, Co-Supervisor
  • Huthoff, Fredrik, Co-Supervisor
Award date2 Dec 2021
Place of PublicationEnschede
Publisher
Print ISBNs978-90-365-5305-6
DOIs
Publication statusPublished - 2 Dec 2021

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