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CLC number: TV88; Q14

On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

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Journal of Zhejiang University SCIENCE A 2008 Vol.9 No.9 P.1229-1238

http://doi.org/10.1631/jzus.A0720079


A two-step approach to investigate the effect of rating curve uncertainty in the Elbe decision support system


Author(s):  Yue-ping XU, Harriette HOLZHAUER, Martijn J. BOOIJ, Hong-yue SUN

Affiliation(s):  Institute of Hydrology and Water Resources, Department of Civil Engineering, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   shy@zju.edu.cn

Key Words:  Elbe decision support system (DSS), Two-step approach, Uncertainty, HEC-6 model


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.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1] Bauer, K.W.Jr., Parnell, G.S., Meyers, D.A., 1999. Response surface methodology as a sensitivity analysis tool in decision analysis. Journal of Multi-criteria Decision Analysis, 8(3):162-180.

[2] Bergström, S., 1995. The HBV Model. In: Singh, V.P. (Ed.), Computer Models of Watershed Hydrology. Water Resources Publications, Littleton, Colorado, p.443-476.

[3] Bevington, P.R., Robinson, D.K., 1992. Data Reduction and Error Analysis for the Physical Sciences. McGraw-Hill, New York, p.96-112.

[4] Booij, M.J., 2002. Appropriate Modelling of Climate Change Impacts on River Flooding. University of Twente, Ph.D Thesis, Enschede, the Netherlands, p.22-30.

[5] de Kok, J.L., Wind, H.G., Delden, H., 2000. Towards a Generic Tool for River Basin Management. Feasibility Assessment for a Prototype DSS for the Elbe. Feasibility Study—Report 2/3, Final Report, University of Twente, Enschede, the Netherlands.

[6] de Kort, I.A.T., Booij, M.J., 2007. Decision making under uncertainty in a decision support system for the Red River. Environmental Modelling and Software, 22(2):128-136.

[7] Draper, D., 1995. Assessment and propagation of model uncertainty. Journal of the Royal Statistical Society Series B, 57(1):45-97.

[8] European Commission, 2000. Communication on the Precautionary Principle, COM. European Commission, DGR, RTD, Eurobarometer 55.2, Europeans, Science and Technology.

[9] Fuchs, E., Giebel, H., Hettrich, A., 2002. Applications of Ecological Models in Water and Navigation Management, the Integrated Model INFORM. NfG Mittelung NR 25, Koblenz (in German).

[10] Giupponi, C., 2007. Decision support systems for implementing the European Water Framework Directive: the MULINO approach. Environmental Modelling and Software, 22(2):248-258.

[11] Jakeman, A.J., Letcher, R.A., Norton, J.P., 2006. Ten iterative steps in development and evaluation of environmental models. Environmental Modelling and Software, 21(5):602-614.

[12] Jamieson, D.G., Fedra, K., 1996. The ‘WaterWare’ decision support system for river basin planning. 1. Conceptual design. Journal of Hydrology, 177(3-4):163-175.

[13] Janssen, P.H.M., Slob, W., Rotmans, J., 1990. Sensitivity Analysis and Uncertainty Analysis: a Survey of Ideas, Method and Techniques. Report No. 958805001, National Institute of Public Health and Environmental Protection, Bilthoven, Dutch.

[14] Kuczera, G., Parent, E., 1998. Monte Carlo assessment of parameter uncertainty in conceptual catchment models: the Metropolis algorithm. Journal of Hydrology, 211:69-85.

[15] Loucks, D.P., da Costa, J.R., 1991. Decision Support Systems, Water Resources Planning. Springer, Berlin, p.1-9.

[16] McIntyre, N.R., Wheater, H.S., 2004. A tool for risk-based analysis of surface water quality. Environmental Modelling and Software, 19(12):1131-1140.

[17] Mowrer, H.T., 2000. Uncertainty in natural resource decision support systems: sources, interpretation, and importance. Computers and Electronics in Agriculture, 27:139-154.

[18] Nestman, F., Buchele, B., 2002. Morphodynamics of the Elbe, Final Report from BMBF—Project with Separate Contributions and Appendix—CD. Kapitel III-2, K., Institut Fur Wasserwirtschaft und Kulturtechnik der Universitat Karlsruhe, Karlsruhe (in German).

[19] Sabatelli, V., Marano, D., Braccio, G., 2002. Efficiency test of solar collectors: uncertainty in the estimation of regression parameters and sensitivity analysis. Energy Conversion and Management, 43(17):2287-2295.

[20] Salewicz, K.A., Nakayama, M., 2004. Development of a web-based decision support system (DSS) for managing large international rivers. Global Environmental Change, 14(1):25-38.

[21] Saltelli, A., Chan, K., Scott, E.M., 2000. Sensitivity Analysis. John Wiley & Sons Ltd., England, p.1-5.

[22] Schlüter, M., Rüger, N., 2007. Application of a GIS-based simulation tool to illustrate implications of uncertainties for water management in the Amudarya River delta. Environmental Modelling & Software, 22(2):158-166.

[23] Sojda, R.S., 2007. Empirical evaluation of decision support systems: needs, definitions, potential methods, and an example pertaining to waterfowl management. Environmental Modelling and Software, 22(2):269-277.

[24] Thorsen, M., Refsgaard, J.C., Hansen, S., 2001. Assessment of uncertainty in simulation of nitrate leaching to aquifers at catchment scale. Journal of Hydrology, 242(3-4):210-227.

[25] UN/WWAP (United Nations/World Water Assessment Program), 2003. UN World Water Development Report: Water for People, Water for Life. UNESCO (United Nations Educational, Scientific and Cultural Organization) and Berghahn Books, Paris, New York and Oxford.

[26] U.S. Army Corps of Engineers, 1993. CPD-6, HEC-6, Scour and Deposition in Rivers and Reservoirs. User’s Manual.

[27] Walker, W.E., Harremoes, P., Rotmans, J., van der Sluijs, J.P., van Asselt M.B.A., Janssen, P., Krayer von Krauss, M.P., 2003. Defining uncertainty, a conceptual basis for uncertainty management in model-based decision support. Integrated Assessment, 4(1):5-17.

[28] Wasserman, L., 2000. Bayesian model selection and model averaging. Journal of Mathematical Psychology, 44(1):92-107.

[29] Xu, Y., 2005. Appropriate Modelling in Decision Support Systems for River Basin Management. Ph.D Thesis, University of Twente, Enschede, the Netherlands.

[30] Xu, Y.P., Booij, M.J., 2005. Propagation of Discharge Uncertainty in a Flood Damage Model for the Meuse River. In: Begum, S., Hall, J., Stive, M. (Eds.), Flood Risk Management in Europe: Innovation in Policy and Practice. Advances in Natural and Technological Hazards Research Series. Springer, Dordrecht, the Netherlands.

[31] Yu, P., Yang, T., Chen, S., 2001. Comparison of uncertainty analysis methods for a distributed rainfall-runoff model. Journal of Hydrology, 244(1-2):43-59.

[32] Zio, E., Apostolakis, G., 1996. Two methods for the structured assessment of model uncertainty by experts in performance assessment of radioactive waste repositories. Reliability Engineering & System Safety, 54(2-3):225-241.

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