Seasonal arima inflow models for reservoir sizing

The reliable sizing of reservoirs is a very important task of hydraulic eng ineering. Although many reservoirs throughout the world have been designed using Rippl's mass curves with historical inflow volumes at the dam site, t his technique is now considered outdated. In this paper, synthetic series o f monthly inflows are used as an alternative to historical inflow records. These synthetic series are generated from stochastic SARIMA (Seasonal Autor egressive Integrated Moving Average) models. The analyzed data refer to the planned Almopeos Reservoir on the Almopeos River in Northern Greece with 1 9-year monthly inflow series. The analysis of this study demonstrates the a bility of SARIMA models, in conjunction with the adequate transformation, t o forecast monthly inflows of one or more months ahead and generate synthet ic series of monthly inflows that preserve the key statistics of the histor ical monthly inflows and their persistence Hurst coefficient K. The forecas ted monthly inflows would be of help in evaluating the optimal real time re servoir operation policies and the generated synthetic series of monthly in flows can be used to provide a probabilistic framework for reservoir design and to cope with the situation where the design horizon of interest exceed s the length of the historical inflow record.