Incorporating likelihood information into multi-objective calibration of conceptual rainfall-runoff models

Alireza NAZEMI, Andrew H.C. CHAN, Xin YAO

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

Abstract

In this paper, the incorporation of parametric likelihood information into NSGAII algorithm has been attempted in order to preserve solutions with more overall likelihood. The crowded comparison operator in NSGA-II, which is used to select the potential solutions for the next generation, is substituted by likelihood comparison operator which includes the consideration of the likelihood information about the potential solutions rather than their distance from each other. As a result the potential solution with higher overall likelihood measure has more chance to be selected in the next generation. Three different scenarios for the estimation of overall likelihood measure are presented. The modified algorithm is used for calibration of two different conceptual rainfall-runoff models in 24 USA MOPEX catchments. The results show that the new modification results to different searching process which can be compared with NSGA-II from different perspectives.
Original languageEnglish
Title of host publicationProc. iEMSs 4th Biennial Meeting - Int. Congress on Environmental Modelling and Software: Integrating Sciences and Information Technology for Environmental Assessment and Decision Making, iEMSs 2008
Pages346-353
Number of pages8
Volume1
Publication statusPublished - 2008
Externally publishedYes

Keywords

  • Likelihood comparison operator
  • Multi-objective calibration
  • NSGA-II
  • Parametric Likelihood
  • Rainfall-Runoff models

Fingerprint

Dive into the research topics of 'Incorporating likelihood information into multi-objective calibration of conceptual rainfall-runoff models'. Together they form a unique fingerprint.

Cite this