Multi-objective global optimization for hydrologic models

Patrice Ogou Yapo, Hoshin Vijai Gupta, Soroosh Sorooshian

Research output: Contribution to journalArticlepeer-review

717 Scopus citations

Abstract

The development of automated (computer-based) calibration methods has focused mainly on the selection of a single-objective measure of the distance between the model-simulated output and the data and the selection of an automatic optimization algorithm to search for the parameter values which minimize that distance. However, practical experience with model calibration suggests that no single-objective function is adequate to measure the ways in which the model fails to match the important characteristics of the observed data. Given that some of the latest hydrologic models simulate several of the watershed output fluxes (e.g. water, energy, chemical constituents, etc.), there is a need for effective and efficient multi-objective calibration procedures capable of exploiting all of the useful information about the physical system contained in the measurement data time series. The MOCOM-UA algorithm, an effective and efficient methodology for solving the multiple-objective global optimization problem, is presented in this paper. The method is an extension of the successful SCE-UA single-objective global optimization algorithm. The features and capabilities of MOCOM-UA are illustrated by means of a simple hydrologic model calibration study.

Original languageEnglish (US)
Pages (from-to)83-97
Number of pages15
JournalJournal of Hydrology
Volume204
Issue number1-4
DOIs
StatePublished - Jan 30 1998

Keywords

  • Calibration
  • Global optimization
  • Multiple objectives
  • Parameter estimation
  • Surface water
  • Watershed models

ASJC Scopus subject areas

  • Water Science and Technology

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