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Prediction of Annual Inflow to Karkheh Dam Reservoir using Time Series Models
* 1 , 2 , 3 , 4
1  PhD candidate of Water Resources Management; Department of Water Engineering, Islamic Azad University, Science and Research Branch, shohadaye hesarak boulevard, university square, end of shahid sattari highway, Tehran, Iran, Postal code : 1477893855, Phon
2  Professor; Head of Department of Water Sciences and Engineering, Islamic Azad University, Science and Research Branch, shohadaye hesarak boulevard, university square, end of shahid sattari highway, Tehran, Iran, Postal code : 1477893855, Phone : 02144865
3  Associate Professor; Department of civil Engineering, Islamic Azad University, Ahvaz Branch, Gollestan boulevard, Farhang Shaher square, Ahvaz, Iran, Postal code: 3733361349, Phone: 06133348336-9, Mobile: +9809121029754
4  Associate Professor; Department of Water Sciences and Engineering, Islamic Azad University, Science and Research Branch, shohadaye hesarak boulevard, university square, end of shahid sattari highway, Tehran, Iran, Postal code: 1477893855, Phone: 021448651

Abstract:

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.

Keywords: ARIMA, reservoir, time series model, Inflow prediction, Karkheh Dam
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