Rainfall-runoff analysis based on competing linear impulse responses: Decomposition of rainfall-runoff processes

Chulsang Yoo, Jooyoung Park

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Many recent studies have successfully used neural networks for non-linear rainfall-runoff modelling. Due to fundamental limitation of linear structures, approaches employing linear models have been generally considered inferior to the neural network approaches in this area. However, the authors believe that with an appropriate extension, the concept of linear impulse responses can be a viable tool since it enables one to understand underlying dynamics of rainfall-runoff processes. In this paper, the use of competing impulse responses for rainfall-runoff analysis is proposed. The proposed method is based on the switch over of competing linear impulse-responses, each of which satisfies the constraints of non-negativity and unimodality. The computational analyses performed for the rainfall-runoff data in the Seolma-Chun experimental basin, Korea showed that the proposed method can yield promising results. Considering the basin characteristics as well as the results from this study, it may be concluded that three impulse responses are enough for rainfall-runoff analysis.

Original languageEnglish
Pages (from-to)660-669
Number of pages10
JournalHydrological Processes
Volume22
Issue number5
DOIs
Publication statusPublished - 2008 Feb 29

Keywords

  • Competing liner impulse responses
  • Neural network
  • Rainfall-runoff analysis

ASJC Scopus subject areas

  • Water Science and Technology

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