Markov chain-based modeling techniques for stochastic generation of daily intermittent streamflows

Abstract

This study is an attempt to generate synthetic daily streamflow data for intermittent streams. The method followed in the study is based on the Markov chain. Two two-state Markov chains or alternatively one three-state Markov chain is proposed for determination of the state of the stream. Ascension curve of the hydrograph is simulated by the two-parameter gamma distribution. Recession curve of the hydrograph is assumed to decay exponentially. Comparison of the statistics of the generated and observed streamflow series shows the applicability of the techniques. Not only long-term statistics such as mean, variance, skewness, and correlation but also short-term features such as the non-invertible shape of the daily streamflow hydrograph are preserved.