Genetic programming approach for flood routing in natural channels

C. Sivapragasam, R. Maheswaran, Veena Venkatesh

Research output: Contribution to journalArticlepeer-review

70 Scopus citations

Abstract

In recognition of the non-linear relationship between storage and discharge existing in most river systems, non-linear forms of the Muskingum model have been proposed, together with methods to calibrate the model parameters. However, most studies have focused only on routing a typical hypothetical flood hydrograph characterized by a single peak. In this study, we demonstrate that the storage-discharge relationship adopted for the non-linear Muskingum model is not adequate for routing flood hydrographs in natural channels, which are often characterized by multiple peaks. As an alternative, an evolutionary algorithm-based modelling approach, i.e. genetic programming (GP), is proposed, which is found to route complex flood hydrographs accurately. The proposed method is applied for constructing a routing model for a channel reach along the Walla Walla River, USA. The GP model performs extremely well with a root-mean-square error (RMSE) of 0.73 m3 s-1 as against an RMSE of 3.26 m3 s-1 for routing the multi-peaked hydrograph. The advantage of GP lies in the fact that, unlike other models, it establishes the routing relationship in an easy and simple mathematical form.

Original languageEnglish (US)
Pages (from-to)623-628
Number of pages6
JournalHydrological Processes
Volume22
Issue number5
DOIs
StatePublished - Feb 29 2008

Keywords

  • Flood routing
  • Genetic algorithm
  • Genetic programming
  • Muskingum method

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