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Multiobjective Automatic Parameter Calibration of a Hydrological Model

1
Research Center for Disaster Prevention Science and Technology, Korea University, Seoul 136-713, Korea
2
School of Civil, Environmental and Architectural Engineering, Korea University, Anam-ro 145, Seongbuk-gu, Seoul 136-713, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Marco Franchini
Water 2017, 9(3), 187; https://doi.org/10.3390/w9030187
Received: 17 October 2016 / Revised: 24 February 2017 / Accepted: 1 March 2017 / Published: 6 March 2017
This study proposes variable balancing approaches for the exploration (diversification) and exploitation (intensification) of the non-dominated sorting genetic algorithm-II (NSGA-II) with simulated binary crossover (SBX) and polynomial mutation (PM) in the multiobjective automatic parameter calibration of a lumped hydrological model, the HYMOD model. Two objectives—minimizing the percent bias and minimizing three peak flow differences—are considered in the calibration of the six parameters of the model. The proposed balancing approaches, which migrate the focus between exploration and exploitation over generations by varying the crossover and mutation distribution indices of SBX and PM, respectively, are compared with traditional static balancing approaches (the two dices value is fixed during optimization) in a benchmark hydrological calibration problem for the Leaf River (1950 km2) near Collins, Mississippi. Three performance metrics—solution quality, spacing, and convergence—are used to quantify and compare the quality of the Pareto solutions obtained by the two different balancing approaches. The variable balancing approaches that migrate the focus of exploration and exploitation differently for SBX and PM outperformed other methods. View Full-Text
Keywords: automatic parameter calibration; multiobjective optimization; NSGA-II; balance between exploration and exploitation; HYMOD model automatic parameter calibration; multiobjective optimization; NSGA-II; balance between exploration and exploitation; HYMOD model
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Jung, D.; Choi, Y.H.; Kim, J.H. Multiobjective Automatic Parameter Calibration of a Hydrological Model. Water 2017, 9, 187.

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