A non-linear perturbation model considering catchment wetness and its application in river flow forecasting

J. Xia, K. M. O'Connor, R. K. Kachroo, G. C. Liang

Research output: Contribution to a Journal (Peer & Non Peer)Articlepeer-review

49 Citations (Scopus)

Abstract

A non-linear perturbation model for river flow forecasting is developed, based on consideration of catchment wetness using an antecedent precipitation index (API). Catchment seasonality, of the form accounted for in the linear perturbation model (the LPM), and non-linear behaviour both in the runoff generation mechanism and in the flow routing processes are represented by a constrained non-linear model, the NLPM-API. A total of ten catchments, across a range of climatic conditions and catchment area magnitudes, located in China and in other countries, were selected for testing daily rainfall-runoff forecasting with this model. It was found that the NLPM-API model was significantly more efficient than the original linear perturbation model (the LPM). However, restriction of explicit non-linearity to the runoff generation process, in the simpler LPM-API form of the model, did not produce a significantly lower value of the efficiency in flood forecasting, in terms of the model efficiency index R2.

Original languageEnglish
Pages (from-to)164-178
Number of pages15
JournalJournal of Hydrology
Volume200
Issue number1-4
DOIs
Publication statusPublished - 15 Dec 1997

Keywords

  • Antecedent precipitation index (API)
  • Catchment wetness
  • Non-linear perturbation model
  • River flow forecasting

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