Markov autocorrelation pulse model for two sites daily streamflow

A Markov autocorrelation pulse (MACP) model for two sites daily streamflow generation is proposed in this study. By using two-component pulses with a one-order Markov autocorrelation deterministic part and a skewed Weibull ra ndom part as inputs to the hydrologic system, a simplified model for daily streamflow generation is formulated. Pulses occurring concurrently at two n eighboring gauges are assumed to be cross-correlated processes. The mean, s tandard deviation, auto- and crosscorrelation of daily, monthly, and annual streamflows are computed for observed and generated flow sequences. The pe rformance of the stochastic streamflow model is evaluated. Results show tha t the MACP model may relatively and satisfactorily reproduce both linear an d nonlinear dependence of daily streamflow processes. The effectiveness of the model is demonstrated through its practical application to the generati on of daily streamflow for the Wupper River in Germany. The significance of the findings reported in this paper is that the MACP model provides a flex ible and adaptive method for reproducing the historical frequency distribut ion of daily streamflow sequence.