Natural Hazards and Earth System Science www.nat-hazards-earth-syst-sci.net 1561-8633 1684-9981 9 4 2009 10.5194/nhess-9-1349-2009 http://www.nat-hazards-earth-syst-sci.net/9/1349/2009/ http://www.nat-hazards-earth-syst-sci.net/9/1349/2009/nhess-9-1349-2009.html http://www.nat-hazards-earth-syst-sci.net/9/1349/2009/nhess-9-1349-2009.pdf 1349 1363 2009-08-06 Planning of technical flood retention measures in large river basins under consideration of imprecise probabilities of multivariate hydrological loads D. Nijssen david.nijssen@rub.de A. Schumann M. Pahlow B. Klein Ruhr-University Bochum, Institute of Hydrology, Water Resources Management and Environmental Engineering, Bochum, Germany As a result of the severe floods in Europe at the turn of the millennium, the ongoing shift from safety oriented flood control towards flood risk management was accelerated. With regard to technical flood control measures it became evident that the effectiveness of flood control measures depends on many different factors, which cannot be considered with single events used as design floods for planning. The multivariate characteristics of the hydrological loads have to be considered to evaluate complex flood control measures. The effectiveness of spatially distributed flood control systems differs for varying flood events. Event-based characteristics such as the spatial distribution of precipitation, the shape and volume of the resulting flood waves or the interactions of flood waves with the technical elements, e.g. reservoirs and flood polders, result in varying efficiency of these systems. Considering these aspects a flood control system should be evaluated with a broad range of hydrological loads to get a realistic assessment of its performance under different conditions. The consideration of this variety in flood control planning design was one particular aim of this study. Hydrological loads were described by multiple criteria. A statistical characterization of these criteria is difficult, since the data base is often not sufficient to analyze the variety of possible events. Hydrological simulations were used to solve this problem. Here a deterministic-stochastic flood generator was developed and applied to produce a large quantity of flood events which can be used as scenarios of possible hydrological loads. However, these simulations imply many uncertainties. The results will be biased by the basic assumptions of the modeling tools. In flood control planning probabilities are applied to characterize uncertainties. The probabilities of the simulated flood scenarios differ from probabilities which would be derived from long time series. With regard to these known unknowns the bias of the simulations was considered by imprecise probabilities. Probabilities, derived from measured flood data were combined with probabilities which were estimated from long simulated series. To consider imprecise probabilities, fuzzy sets were used to distinguish the results between more or less possible design floods. The need for such a differentiated view on the performance of flood protection systems is demonstrated by a case study. % vor jede Referenz Berlekamp, J., Zerger, A., Lauterbach, S., Graf, N., Matthies, M., and Argent, R. M.: A decision support system for integrated river basin management of the German Elbe, Australia, Modelling and Simulation Society of Australia and New Zealand Inc., 2005. % vor jede Referenz Beven, K. J.: On undermining the science?, Hydrol. Process., 20, 3141–3146, 2006. % vor jede Referenz Blazkova, S. and Beven, K.: Flood frequency estimation by continous simulation for a catchment treated as ungauged (with uncertainty), Water Resour. Res., 38, 1139, doi:10.1029/2001WR000500, 2002. % vor jede Referenz Boender, C. G. E., De Graan, J. G., and Lootsma, F. A.: Multicriteria decision analysis with fuzzy pairwise comparison, Fuzzy Set. Syst., 29, 133–143, 1989. % vor jede Referenz Chang, D.-Y.: Applications of the extent analysis method on fuzzy AHP, Eur. J. Oper. Res., 95, 649–655, 1996. % vor jede Referenz Cameron, D. S., Beven, K. J., Tawn, J., Blazkova, S., and Naden, P.: Flood frequency estimation by continuous simulation for a gauged upland catchment (with uncertainty), J. Hydrol., 219, 169–187, 1999. % vor jede Referenz Deng, H.: Multicriteria analysis with fuzzy pairwise comparison, the treatment of uncertainity in artificial intelligence, Int. J. Approx. Reason., 21, 215–232, 1999. % vor jede Referenz Favre, A. C., El Adlouni, S., Perreault, L., Thiemonge, N., and Bobee, B.: Multivariate hydrological frequency analysis using copulas, Water Resour. Res., 40, 1–12, W01101, 2004. % vor jede Referenz Fell, R. and Hartford, D.: Landslide Risk Management, in: Landslide Risk Assessment, edited by: Cruden, D. and Fell, R., Balkema, 51–110, 1997. % vor jede Referenz Genest, C. and Favre, A. C.: Everything you always wanted to know about copula modeling but were afraid to ask, J. Hydrol. Eng., 12(4), 347–368, 2007. % vor jede Referenz Grimaldi, S. and Serinaldi, F.: Asymmetric copula in multivariate flood frequency analysis, Adv. Water Resour., 29(8), 1155–1167, 2006. % vor jede Referenz Haimes, Y. Y.: Risk analysis of fracture and failure, Mater. Res. Innov., 2, 16–21, 1998. % vor jede Referenz Hundecha, Y., Pahlow, M., Klein, B., and Schumann, A.: Modelling of daily rainfall for flood risk assessment using a mixed distribution, Water Resour. Res., submitted , 2009. % vor jede Referenz Joe, H.: Multivariate Models and Dependence Concepts, Chapman and Hall, New York, 1997. % vor jede Referenz Kachroo, R. K.: Storage required to augment low flows – a regional study, Hydrolog. Sci. J., 37, 247–261, 1992. % vor jede Referenz Kamrath, P., Disse, M., Hammer, M. and Köngeter, J.: Assessment of discharge through a dike breach and simulation of flood wave propagation, Nat. Hazards, 38, 63–78, 2006. % vor jede Referenz Klein, B., Pahlow, M., Hundecha, Y., and Schumann, A.: Probability analysis of hydrological loads for the design of flood control systems using copulas, J. Hydrol. Eng., submitted 2009. % vor jede Referenz Klir, G. J. and Smith, R. M.: On measuring uncertainty and uncertainty-based information: Recent developments, Ann. Math. Artif. Intel., 32, 5–33, 2001. % vor jede Referenz Koutsoyiannis, D. and Onof, C.: Rainfall disaggregation using adjusting procedures on a Poisson cluster model, J. Hydrol., 246, 109–122, 2001. % vor jede Referenz Koutsoyiannis, D., Onof, C., and Weather, H.: Multivariate rainfall disaggregation at a fine time scale, Water Resour. Res., 39(7), 1173, doi:10.1029/2002WR001600, 2003. % vor jede Referenz Krupnick, A., Morgenstern, R., Batz, M., Nelson, P., Burtraw, D., Shih, J.-S., and McWilliams, M.: Not a Sure Thing: Making Regulatory Choices Under Uncertainty, Resources for the Future, Washington, DC, 233 pp., 2006. % vor jede Referenz Lamb, R.: Confidence intervals for a spatially generalized, continuous simulation flood frequency model for Great Britain, Water Resour. Res., 40, W07501, doi:10.1029/2003WR002428, 2004. % vor jede Referenz Lindström, G., Johansson, B., Persson, M., Gardelin, M., and Bergström, S.: Development and test of the distributed HBV-96 model, J. Hydrol., 201, 272–288, 1997. % vor jede Referenz McMillan, H. K. and Brasington, J.: End-to-end flood risk assessment: A coupled model cascade with uncertainty estimation, Water Resour. Res., 44, W03419, doi:10.1029/2007WR005995, 2008. % vor jede Referenz Merz, B.: Hochwasserrisiken, Grenzen und Möglichkeiten der Risikoabschätzung, E. Schweizerbart'sche Verlagsbuchhandlung (Nägele u. Obermiller) Stuttgart, 2006. % vor jede Referenz Merz, B. and Thieken, A.: Die Bedeutung von extremen Ereignissen in der Risikoquantifizierung, ÖWAV-Seminar 2007, TU Wien, 117–131, 2007. % vor jede Referenz Morss, R. E.: Flood Risk, Uncertainty, and Scientific Information for Decision Making – Lessons from an Interdisciplinary Project, American Meteorological Society, B. Am. Meteorol. Soc., 86(11), 1593–1602, doi:10.1175/BAMS-86-11-1593, 2005. % vor jede Referenz Nelsen, R. B.: An Introduction to Copulas, Springer, New York, 1999. % vor jede Referenz Plate, E. J. and Meon, G.: Stochastic aspects of dam safety analysis, Proc. Of JSCE, No. 393/II-9 (Hydraulic and Sanity Eng.), 1–8, 1988. % vor jede Referenz Plate, E. J.: Flood risk and flood management, J. Hydrol., 267, 2–11, 2002. % vor jede Referenz Saaty, T. L.: The analytic hierarchy process – planning, priority setting, resource allocation, 1980. % vor jede Referenz Salvadori, G. and De Michele, C.: Frequency analysis via copulas: Theoretical aspects and applications to hydrological events, Water Resour. Res., 40(12), W12511, doi:10,1029/2004WR003133, 2004. % vor jede Referenz Salvadori, G., De Michele, C., Kottegoda, N. T., and Rosso, R.: Extremes in Nature: An Approach Using Copulas, Springer, Dordrecht, 2007. % vor jede Referenz Sklar, A.: Fonctions de reparttion à n dimensions et leura Marges, Publ. Inst. Stat. Univ. Paris, 8, 220–231, 1959. % vor jede Referenz Slovic, P. and Weber, E. U.: Perception of Risk Posed by Extreme Events, Risk Management strategies in an Uncertain World, Columbia University and Wissenschaftskolleg zu Berlin, New York, 1–21, 2002. % vor jede Referenz Srdjevic, B. and Medeiros, Y.: Fuzzy AHP Assessment of Water Management Plans, Water Resour. Manag., 22, 877–894, 2008. % vor jede Referenz Thieken, A. H., Kreibich, H.,Müller, M., and Merz, B.: Coping with floods: preparedness, response and recovery of flood-affected residents in Germany in 2002, Hydrolog. Sci. J., 52, 1016–1037, 2007. % vor jede Referenz Van Laarhoven, P. J. M. and Pedrycz, W.: A fuzzy extension of Saaty's priority theory, Fuzzy Set. Syst., 11, 229–241, 1983. % vor jede Referenz Walley, P.: Statistical Reasoning with Imprecise Probabilities, Chapman and Hall, London, 1991. % vor jede Referenz Zadeh, L. A.: Fuzzy Sets, Information and Control, 8, 338–353, 1965. % vor jede Referenz Zadeh, L. A.: Probability measures of Fuzzy Events, J. Math. Anal. Appl., 23, No. 2, August 1968. % vor jede Referenz Zadeh, L. A.: Toward a generalised theory of uncertainty (GTU) – an outline, Inform. Sciences, 172, 1–40, 2005.