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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 16, issue 2
Hydrol. Earth Syst. Sci., 16, 603–629, 2012
https://doi.org/10.5194/hess-16-603-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 16, 603–629, 2012
https://doi.org/10.5194/hess-16-603-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 27 Feb 2012

Research article | 27 Feb 2012

Towards a more representative parametrisation of hydrologic models via synthesizing the strengths of Particle Swarm Optimisation and Robust Parameter Estimation

T. Krauße and J. Cullmann

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Cited articles

Beven, K. and Binley, A.: The future of distributed models: Model calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, https://doi.org/10.1002/hyp.3360060305, 1992.
Brakensiek, D., Rawls, W., and Stephenson, G.: Modifying SCS hydrological soil groups and curve numbers for rangeland soils, ASAE Paper, PNR-84-203, St. Joseph/ Michigan, 1984. % unfortunately in our print and available online sources no page numbers available
Bremner, D., Chen, D., Iacono, J., Langerman, S., and Morin, P.: Output-sensitive algorithms for Tukey depth and related problems, Stat. Comput., 18, 259–266, 2008.
Bárdossy, A. and Singh, S. K.: Robust estimation of hydrological model parameters, Hydrol. Earth Syst. Sci., 12, 1273–1283, https://doi.org/10.5194/hess-12-1273-2008, 2008.
Cabrera, J. C. F. and Coello, C. A.: Multi-Objective Swarm Intelligent Systems, vol. 261 of Studies in Computational Intelligence\/, chap. Micro-MOPSO: A Multi-Objective Particle Swarm Optimizer that Uses a Very Small Population Size, p. 218, Springer Verlag, 2010.
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