The optimal exploitation of water from a dam reservoir requires a comprehensive knowledge of future availability of water resources. In this case the amount of water that will be available in the future is important. Also, we need to examine the flows at the dam from a short-term perspective. This is necessary to avoid overflowing and to minimize damage. In order to facilitate forecasting of the water resources, many different techniques have been developed through the years. In this paper, using annual mean flow data (since 1958-2005) obtained from jelogir majin Hydrometric station at Karkheh River (upstream of Karkheh Dam), the Auto Regressive Integrated Moving average (ARIMA) model, for prediction of annual mean inflow to Karkheh Dam reservoir was accomplished. On the basic of comparison the results of the model with measured data, the performance of ARIMA (4, 1, 1) model by conditional least square (CLS) estimation parameter method is acceptable.The SAS and SPSS softwares were used to implement of the models.
Prediction of Annual Inflow to Karkheh Dam Reservoir using Time Series Models
Published: 05 November 2017 by MDPI in First International Electronic Conference on the Hydrological Cycle session Water Resources Management
Keywords: ARIMA, reservoir, time series model, Inflow prediction, Karkheh Dam