Propagation of Discharge Uncertainty in A Flood Damage Model for the Meuse River


Xu, Yueping and Booij, Martijn J. (2007) Propagation of Discharge Uncertainty in A Flood Damage Model for the Meuse River. In: Selina Begum & Marcel J.F. Stive & Jim W. Hall (Eds.), Flood risk management in Europe : innovation in policy and practice. Springer, Dordrecht, pp. 293-310. ISBN 9781402041990

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Abstract:Uncertainty analysis plays an important role in the decision- making process. It
can give decision makers a complete idea of how different measures will affect the whole
river system. Thus it helps decision makers to make a better choice among measures in a
more systematic manner. In case of flood damage reduction projects, uncertainty analysis
helps to evaluate the main decision criterion – expected annual damage. The aim of this paper
is to investigate the propagation of discharge uncertainty, which is one of the main uncertainty
sources in a damage model, into expected annual damage. The discharge uncertainty
considered here includes model uncertainty (choice of different probability distributions) and
sampling errors due to finite gauge record lengths. The calculated uncertainty in the discharge
varies between 17 percent for a return period of 5 year and 30 percent for a return period of
1250 year. A first order method is used here to explore the role of discharge uncertainty in the
expected annual damage model. The results from the damage model indicate that both model
uncertainty and sampling errors are important, with the latter being somewhat more important.
The Log-Pearson Type 3 gives a much smaller uncertainty range of the expected annual
damage than the other three distribution models used. The uncertainty is aggravated when
propagated into the damage results. The uncertainty in the damage reduces a great amount
when the sample size increases to n=80. The results derived from the first order method in
fact give two bounds of uncertainty, which is an overestimate in this case.
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Engineering Technology (CTW)
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