Fitting hydrological models on multiple responses using the multiobjective evolutionary annealing simplex approach

A. Efstratiadis, and D. Koutsoyiannis, Fitting hydrological models on multiple responses using the multiobjective evolutionary annealing simplex approach, Practical hydroinformatics: Computational intelligence and technological developments in water applications, edited by R.J. Abrahart, L. M. See, and D. P. Solomatine, 259–273, doi:10.1007/978-3-540-79881-1_19, Springer, 2008.



Most complex hydrological modelling schemes, when calibrated on a single observed response (e.g. river flow at a point), provide poor predictive capability, due to the fact that the rest of variables of basin response remain practically uncontrolled. Current advances in modelling point out that it is essential to take into account multiple fitting criteria, which correspond to different observed responses or to different aspects of the same response. This can be achieved through multiobjective calibration tools, thus providing a set of solutions rather than a single global optimum. Besides, actual multiobjective optimization methods are rather inefficient, when real-world problems with many criteria and many control variables are involved. In hydrological applications there are some additional issues, due to uncertainties related to the representation of complex processes and the observation errors. The multiobjective evolutionary annealing-simplex (MEAS) method implements an innovative scheme, particularly developed for the optimization of such problems. Its features and capabilities are illustrated by solving a challenging parameter estimation problem, dealing with hydrological modelling and water resources management in a karstic basin in Greece.

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Our works referenced by this work:

1. A. Efstratiadis, and D. Koutsoyiannis, An evolutionary annealing-simplex algorithm for global optimisation of water resource systems, Proceedings of the Fifth International Conference on Hydroinformatics, Cardiff, UK, 1423–1428, doi:10.13140/RG.2.1.1038.6162, International Water Association, 2002.
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5. A. Efstratiadis, and D. Koutsoyiannis, The multiobjective evolutionary annealing-simplex method and its application in calibrating hydrological models, European Geosciences Union General Assembly 2005, Geophysical Research Abstracts, Vol. 7, Vienna, 04593, doi:10.13140/RG.2.2.32963.81446, European Geosciences Union, 2005.
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Our works that reference this work:

1. A. Efstratiadis, I. Nalbantis, A. Koukouvinos, E. Rozos, and D. Koutsoyiannis, HYDROGEIOS: A semi-distributed GIS-based hydrological model for modified river basins, Hydrology and Earth System Sciences, 12, 989–1006, doi:10.5194/hess-12-989-2008, 2008.
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4. I. Tsoukalas, P. Kossieris, A. Efstratiadis, and C. Makropoulos, Surrogate-enhanced evolutionary annealing simplex algorithm for effective and efficient optimization of water resources problems on a budget, Environmental Modelling and Software, 77, 122–142, doi:10.1016/j.envsoft.2015.12.008, 2016.

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Other works that reference this work (this list might be obsolete):

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