A model for daily flows of intermittent streams

Hafzullah Aksoy*, Mehmetik Bayazit

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

46 Citations (Scopus)

Abstract

A stochastic model for synthetic data generation is not available in the literature for daily flows of intermittent streams. Such a model is required in the planning and operation of structures on an intermittent stream for purposes where short time f low fluctuations are important. In this study a model is developed for such a case. The model consists of four steps: determination of the days on which flow occurs, determination of the days on which a flow increment occurs, determination of the magnitude of the flow increment, and calculation of the flow decrement on days when the flow is reduced. The first two steps are modelled by a three-state Markov chain. In the third step, flow increments on the rising limb of the hydrograph are assumed to be gamma distributed. In the last step an exponential recession is used with two different coefficients. Parameters of the model are estimated from the observed daily streamflow data for each month of the year. The model is applied to a daily flow series of 35 years' length. It is seen that the model can preserve the short-term characteristics (the ascension and recession curves and peaks) of the hydrograph in addition to the long-term characteristics (mean, variance, skewness, lag-one and higher lag au tocorrelation coefficients, and zero flow percentage). The number of parameters of the model can be decreased by fitting Fourier series to their annual variation. Copyright (C) 2000 John Wiley and Sons, Ltd.

Original languageEnglish
Pages (from-to)1725-1744
Number of pages20
JournalHydrological Processes
Volume14
Issue number10
DOIs
Publication statusPublished - 2000

Keywords

  • Daily flows
  • Intermittent streams
  • Markov chains
  • Mathematical modelling
  • Stochastic modelling

Fingerprint

Dive into the research topics of 'A model for daily flows of intermittent streams'. Together they form a unique fingerprint.

Cite this