A Multicriteria Approach to Risk Analysis

Part I: Framework
  • Pieter van Gelder
  • Lucien Duckstein
  • Eric Parent
Conference paper


Risk identification consists of defining the hazard, loss-causing event E, probability P(E) of that event, perception Pe(E,P(E)) and consequences C(Pe) of that perception. Risk identification is followed by risk management, whose purpose is to mitigate the risks, for example by reducing P(E) or C(Pe) and providing suitable risk communication to the population at risk. Since managing risk has a financial cost, that cost should be traded off with risk severity or frequency — hence a bi-objective model is naturally called for. Furthermore, several risks may exist, thus a risk-risk tradeoff constitutes a multicriterion decision (MCDA) procedure as shown in part I of this paper. These points are illustrated using hydrologic examples in part II.


Water Resource System Risk Identification Bayesian Decision Theory Multicriteria Approach Probabilistic Safety Assessment 
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  1. 1.
    Duckstein L. A systems framework for risk and reliability applied to hydrologic design and operation. In: Benedini M, Andah K and Harboe R (eds), Water Resources Management: Modern Decision Techniques, pp 29–57, Balkema, Rotterdam, 1992Google Scholar
  2. 2.
    Kazanowski A. D. A Standardized Approach to Cost-Effectiveness Evaluations. In: English, JM (ed), Cost-effectiveness: the Economic Evaluation of Engineering Systems, pp. 113–115, John Wiley and Sons Inc., New York, 1968Google Scholar
  3. 3.
    Davis, DR, Kisiel C. and Duckstein L. Bayesian decision theory applied to design in hydrology. Water Resources Research, Vol. 8, No. 1, pp. 33–41, 1972CrossRefGoogle Scholar
  4. 4.
    Bernier J. Quantitative analysis of uncertainties in water resources. Application for predicting the effects of changes. In: Duckstein L, Parent E (eds.) Engineering Reliability and Risk in Natural Resources Management (with special references to hydrosystems under changes of physical or climatic environment). NATO ASI Series E, Vol. 275, pp. 343–358, Dordrecht, The Netherlands, 1994Google Scholar
  5. 5.
    Roy, B, Multicriteria Methodology for Decision Aiding. Kluwer, Dordrecht, 1996CrossRefMATHGoogle Scholar
  6. 6.
    Bogardi JJ, Duckstein L. Interactive multiobjective analysis embedding the decision maker’s implicit preference function. Water Resources Bulletin, 28(1): 78–88, Jan. 1992CrossRefGoogle Scholar
  7. 7.
    Monarchi D, Kisiel C, Duckstein L. Interactive Multiobjective Programming in Water Resources: A Case Study, Water Resources Research. Vol. 9, No. 4, pp. 837–850, 1973CrossRefGoogle Scholar
  8. 8.
    Loucks DP, Stedinger JR, Haith DA. Water Systems Planning and Analysis, pp. 569, Prentice-hall, Englewood Cliffs, N. J., 1978Google Scholar

Copyright information

© Springer-Verlag London 2004

Authors and Affiliations

  • Pieter van Gelder
    • 1
  • Lucien Duckstein
    • 2
  • Eric Parent
    • 2
  1. 1.Faculty of Civil Engineering and GeosciencesDelft University of TechnologyDelftThe Netherlands
  2. 2.Ecole Nationale du Genié Rural des eaux et des Forêts (ENGREF)Laboratoire Gestion du Risque En Science de l’Eau (GRESE)France

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