Author(s): Camilo A. S. De Farias; Koichi Suzuki; Alcigeimes B. Celeste; Akihiro Kadota
Keywords: Multivariate stochastic simulation; Reservoir inflow; Groundwater level
Abstract: Many studies have been carried out in order to produce measures capable of ensuring the sustainable use of the water resources. A better management of water resources systems can be achieved if the long term information of hydrologic variables is available, which is not always the case. Stochastic simulation of such hydrologic variables is an attractive alternative to extend the length of observed records. This paper implements and applies a multivariate autoregressive model for simulating daily stochastic series of reservoir inflows and groundwater levels in the city of Matsuyama, Japan. The stochastic generated series must keep not only the statistical features and seasonal oscillations of their respective observed series but also the interrelation properties between their values. Ten years of observed reservoir inflows and groundwater levels were used for calibrating the model parameters. The results show that the model preserves the major statistical properties between the variables as well as the cross-correlation coefficients.