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Seasonal prediction of Karoon streamflow using large-scale climate indices

Azimi, M ; Sharif University of Technology | 2011

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  1. Type of Document: Article
  2. DOI: 10.1061/41173(414)122
  3. Publisher: 2011
  4. Abstract:
  5. Water resources limitation in arid and semi arid regions on one hand and water demand increase on the other, have made the optimum utilization of existing water resources and systems necessary. In this context, researchers are trying to increase the accuracy and lag time of prediction by using various statistic and empirical models as well as different local and long-range variables in the last decades. Karoon River is the greatest and most important river in Iran because of agricultural water demand supply and hydroelectric power production. Therefore streamflow prediction of this river has considerable economical and social benefits. In this study the relationship between Karoon stramflow and monthly customary climate phenomena (ENSO, PDO and NAO) indices and rainfall data has been discussed. Also, to predict the dry season streamflow (April to August) in Poleshaloo hydrometry station, entrance to the Karoon3 Reservoir in the beginning of April, a multiple linear regression model based on principal component analysis (PCA) has been developed. The results indicate that Karoon River annual and seasonal water volume has a significant correlation with the PDO and SOI Indices. In addition, the explained model can predict streamflow with an accuracy of 20 mean absolute percentile error in verification period
  6. Keywords:
  7. Agricultural water ; Arid and semi-arid regions ; Climate index ; Climates ; Dry seasons ; Empirical model ; Hydroelectric power production ; Iran ; Karoon River ; Lag-time ; Multiple linear regression models ; Predictions ; Rainfall data ; Seasonal prediction ; Social benefits ; SOI indices ; Streamflow prediction ; Water demand ; Water volumes ; Arid regions ; Bearings (structural) ; Climatology ; Forecasting ; Hydroelectric power ; Linear regression ; Principal component analysis ; Reservoirs (water) ; Rivers ; Stream flow ; Sustainable development ; Water resources
  8. Source: World Environmental and Water Resources Congress 2011: Bearing Knowledge for Sustainability - Proceedings of the 2011 World Environmental and Water Resources Congress, 22 May 2011 through 26 May 2011 ; May , 2011 , Pages 1184-1193 ; 9780784411735 (ISBN)
  9. URL: http://ascelibrary.org/doi/abs/10.1061/41173%28414%29122