Advances in Geosciences www.adv-geosci.net 1680-7340 1680-7359 11 Large-scale hydrological modelling and the European Union water policies 2007 10.5194/adgeo-11-117-2007 http://www.adv-geosci.net/11/117/2007/ http://www.adv-geosci.net/11/117/2007/adgeo-11-117-2007.html http://www.adv-geosci.net/11/117/2007/adgeo-11-117-2007.pdf 117 122 2007-06-20 Identifying and reducing model structure uncertainty based on analysis of parameter interaction Y. Wang yan.wang-2@rub.de J. Dietrich F. Voss M. Pahlow Institute of Hydrology, Water Resources Management and Environmental Engineering, Ruhr-University Bochum, 44801 Bochum, Germany Multi-objective optimization algorithms are widely used for the calibration of conceptual hydrological models. Such algorithms yield a set of Pareto-optimal solutions, reflecting the model structure uncertainty. In this study, a multi-objective optimization strategy is suggested, which aims at reducing the model structure uncertainty by considering parameter interaction within Pareto-optimal solutions. The approach has been used to develop a nested setup of a rainfall-runoff model, which is integrated in a probabilistic meso-/macroscale flood forecasting system. The optimization strategy aided in determining the best combination of a lumped (computationally efficient in operational real time forecasting) and a semi-distributed parameterization of the hydrological model. First results are shown for two subbasins of the Mulde catchment in Germany. The different phenomena of parameter interaction were analysed in this case study to reduce the model structure uncertainties. Becker, A., Kloecking, B., Lahmer, W., and Pfuetzner, B.: The hydrological modelling system Arc/EGMO, in: Mathematical models of large watershed hydrology, edited by: Singh, V. P. and Frevert, D. K, Water Resources Publ., Highlands Ranch, Colorado, USA, 321–384, 2002. Chappell, N. A., Bidin, K., Sherlock, M. D., and Lancaster, J. W.: Parsimonious spatial representation of tropical soils within dynamic, rainfall-runoff models, in: Forests-Water-People in the Humid Tropics, Cambridge University Press, Cambridge, 85–98, 2004. Duan, Q., Gupta, V. K., and Sorooshian, S.: Effective and efficient global optimization for conceptual rainfall-runoff models, Water Resour. Res., 28, 1015–1031, 1992. Duan, Q., Gupta, V. K., and Sorooshian, S.: A shuffled complex evolution approach for effective and efficient global minimization, J. of Optimization Theory and Applications, 76(3), 501–521, 1993. Fenicia, F., Savenije, H. H. G., Matgen, P., and Pfister, L.: A comparison of alternative multi-objective calibration strategies for hydrological modeling, Water Resour. Res, 43, W03434, doi:10.1029/2006WR005098, 2007. Gupta, H. V., Sorooshian, S., and Yapo, P. O.: Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information, Water Resour. Res, 34(4), 751–764, 1998. Hogue, T. S., Gupta, H. V., Sorooshian, S., and Tomkins, C. D.: A multi-step automatic calibration scheme for watershed models, Calibration of watershed models, Water Sci. Appl., 6, 165–174, 2003. Vrugt, J. A., Bouten, W., Gupta, H. V., and Sorooshian, S.: A shuffled complex evolution Metropolis algorithm for optimization and uncertainty assessment of hydrological model parameters, Water Resour. Res, 39(8), 1201, doi: 10.1029/2002WR001642, 2003a. Vrugt, J. A., Gupta, H. V., Bastidas, L. A., Bouten, W., Sorooshian, S.: Effective and efficient algorithm for multiobjective optimization of hydrologic models, Water Resour. Res., 39(8), 1214, doi:10.1029/2002WR001746, 2003b. Yapo, P. O., Gupta, H. V., and Sorooshian, S.: Multi-objective global optimization for hydrologic models, J. Hydrol., 204, 83–97, 1998.