CLC number: TV88; Q14
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
Cited: 1
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Yue-ping XU, Harriette HOLZHAUER, Martijn J. BOOIJ, Hong-yue SUN. A two-step approach to investigate the effect of rating curve uncertainty in the Elbe decision support system[J]. Journal of Zhejiang University Science A, 2008, 9(9): 1229-1238.
@article{title="A two-step approach to investigate the effect of rating curve uncertainty in the Elbe decision support system",
author="Yue-ping XU, Harriette HOLZHAUER, Martijn J. BOOIJ, Hong-yue SUN",
journal="Journal of Zhejiang University Science A",
volume="9",
number="9",
pages="1229-1238",
year="2008",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A0720079"
}
%0 Journal Article
%T A two-step approach to investigate the effect of rating curve uncertainty in the Elbe decision support system
%A Yue-ping XU
%A Harriette HOLZHAUER
%A Martijn J. BOOIJ
%A Hong-yue SUN
%J Journal of Zhejiang University SCIENCE A
%V 9
%N 9
%P 1229-1238
%@ 1673-565X
%D 2008
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A0720079
TY - JOUR
T1 - A two-step approach to investigate the effect of rating curve uncertainty in the Elbe decision support system
A1 - Yue-ping XU
A1 - Harriette HOLZHAUER
A1 - Martijn J. BOOIJ
A1 - Hong-yue SUN
J0 - Journal of Zhejiang University Science A
VL - 9
IS - 9
SP - 1229
EP - 1238
%@ 1673-565X
Y1 - 2008
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A0720079
Abstract: For river basin management, the reliability of the rating curves mainly depends on the accuracy and time period of the observed discharge and water level data. In the elbe decision support system (DSS), the rating curves are combined with the HEC-6 model to investigate the effects of river engineering measures on the Elbe River system. In such situations, the uncertainty originating from the HEC-6 model is of significant importance for the reliability of the rating curves and the corresponding DSS results. This paper proposes a two-step approach to analyze the uncertainty in the rating curves and propagate it into the Elbe DSS: analytic method and Latin Hypercube simulation. Via this approach the uncertainty and sensitivity of model outputs to input parameters are successfully investigated. The results show that the proposed approach is very efficient in investigating the effect of uncertainty and can play an important role in improving decision-making under uncertainty.
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