One decade of multiobjective calibration approaches in hydrological modelling: a review

A. Efstratiadis, and D. Koutsoyiannis, One decade of multiobjective calibration approaches in hydrological modelling: a review, Hydrological Sciences Journal, 55 (1), 58–78, doi:10.1080/02626660903526292, 2010.



One decade after the first publications on multiobjective hydrological calibration, we summarize the experience gained so far, by underlining the key perspectives offered by such approaches to improve parameter identifiability. After reviewing the fundamentals of vector optimization theory and the algorithmic issues, we link the multicriteria calibration approach with the concepts of uncertainty and equifinality. Specifically, the multicriteria framework enables recognizing and handling errors and uncertainties, and detecting prominent behavioural solutions with acceptable trade-offs. Particularly in models of complex parameterization, a multiobjective approach becomes essential for improving the identifiability of parameters and augmenting the information contained in calibration, by means of both multiresponse measurements and empirical metrics (“soft” data), which account for the hydrological expertise. Based on the literature review, we also provide alternative techniques to treat with conflicting and non-commeasurable criteria, and hybrid strategies to utilize the information gained towards identifying promising compromise solutions that ensure consistent and reliable calibrations.

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Our works referenced by this work:

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Our works that reference this work:

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11. G. Papacharalampous, H. Tyralis, A. Langousis, A. W. Jayawardena, B. Sivakumar, N. Mamassis, A. Montanari, and D. Koutsoyiannis, Probabilistic hydrological post-processing at scale: Why and how to apply machine-learning quantile regression algorithms, Water, doi:10.3390/w11102126, 2019.
12. G. Papacharalampous, D. Koutsoyiannis, and A. Montanari, Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: Methodology development and investigation using toy models, Advances in Water Resources, 136, 103471, doi:10.1016/j.advwatres.2019.103471, 2020.
13. G. Papacharalampous, H. Tyralis, D. Koutsoyiannis, and A. Montanari, Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: A large-sample experiment at monthly timescale, Advances in Water Resources, 136, 103470, doi:10.1016/j.advwatres.2019.103470, 2020.
14. R. Ioannidis, N. Mamassis, A. Efstratiadis, and D. Koutsoyiannis, Reversing visibility analysis: Towards an accelerated a priori assessment of landscape impacts of renewable energy projects, Renewable and Sustainable Energy Reviews, 161, 112389, doi:10.1016/j.rser.2022.112389, 2022.
15. A. Efstratiadis, and G.-K. Sakki, Revisiting the management of water-energy systems under the umbrella of resilience optimization, e-Proceedings of the 5th EWaS International Conference, Naples, 596–603, 2022.
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17. S. Tsattalios, I. Tsoukalas, P. Dimas, P. Kossieris, A. Efstratiadis, and C. Makropoulos, Advancing surrogate-based optimization of time-expensive environmental problems through adaptive multi-model search, Environmental Modelling and Software, 162, 105639, doi:10.1016/j.envsoft.2023.105639, 2023.
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