Multiobjective automatic parameter calibration of a hydrological model

Donghwi Jung, Young Hwan Choi, Joong Hoon Kim

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number187
JournalWater (Switzerland)
Volume9
Issue number3
DOIs
Publication statusPublished - 2017

Fingerprint

hydrologic models
Calibration
calibration
mutation
Mutation
exploitation
Polynomials
Mississippi
Benchmarking
Rivers
sorting
peak flow
Sorting
diversification
genetic algorithm
spatial distribution
spacing
Genetic algorithms
rivers
river

Keywords

  • Automatic parameter calibration
  • Balance between exploration and exploitation
  • HYMOD model
  • Multiobjective optimization
  • NSGA-II

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Biochemistry
  • Aquatic Science
  • Water Science and Technology

Cite this

Multiobjective automatic parameter calibration of a hydrological model. / Jung, Donghwi; Choi, Young Hwan; Kim, Joong Hoon.

In: Water (Switzerland), Vol. 9, No. 3, 187, 2017.

Research output: Contribution to journalArticle

@article{ec2b8e3e87de43b594bf5b37d1f77994,
title = "Multiobjective automatic parameter calibration of a hydrological model",
abstract = "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.",
keywords = "Automatic parameter calibration, Balance between exploration and exploitation, HYMOD model, Multiobjective optimization, NSGA-II",
author = "Donghwi Jung and Choi, {Young Hwan} and Kim, {Joong Hoon}",
year = "2017",
doi = "10.3390/w9030187",
language = "English",
volume = "9",
journal = "Water (Switzerland)",
issn = "2073-4441",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "3",

}

TY - JOUR

T1 - Multiobjective automatic parameter calibration of a hydrological model

AU - Jung, Donghwi

AU - Choi, Young Hwan

AU - Kim, Joong Hoon

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

KW - Automatic parameter calibration

KW - Balance between exploration and exploitation

KW - HYMOD model

KW - Multiobjective optimization

KW - NSGA-II

UR - http://www.scopus.com/inward/record.url?scp=85014962022&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85014962022&partnerID=8YFLogxK

U2 - 10.3390/w9030187

DO - 10.3390/w9030187

M3 - Article

VL - 9

JO - Water (Switzerland)

JF - Water (Switzerland)

SN - 2073-4441

IS - 3

M1 - 187

ER -