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:: Volume 30, Issue 2 (2015) ::
geores 2015, 30(2): 261-274 Back to browse issues page
Evaporation Predict Using Climate Signals and Artificial Neural Network in Dez Basin
Enayatollah Rahmati *1, Majid Montazeri2, Amir Gandomkar, Mehran Lshanizand3
1- Department Of Climatology, Islamic Azad University,Najaf Abad,Iran , Enayat51@yahoo.com
2- Department Of Climatology ,Isfahan University ,Isfahan,Iran
3- Lorestan Agriculture Research Center,Lorestan,Iran
Abstract:   (968 Views)
Evaporation is an important phenomenon in Hydrological cycle and estimation and prediction is necessary for proper planning and management of water, so to predict it's occurred has been in Dez basin that significant part of the water supplies. The simulated evaporation and the possibility of prediction it, using neural network that data of evaporation at 4 station and claimant signals whit at least 19 years monthly analysis. The results show that the most important signals affecting the evaporation basin include: Nina3, Nina1, Sw monsoon, Mei, Nina4 and Nina3.4. Comparison of observed data with a high correlation between the ANN output data shows. So that the correlation of the Khorramabad station is 79%, Dezful 94%, Kuhrang 80%, and Arak 72%. The output data of the neural network and climatic signals, can accurately predict the top 98% of the basin evaporation.
Keywords: Predict, Evaporation, Climate Signals, Artificial Neural Network, Dez Basin .
     
Article Type: Original Research | Subject: Special
Received: 2014/04/7 | Accepted: 2015/02/14 | Published: 2015/09/21
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Rahmati E, Montazeri M, Gandomkar A, Lshanizand M. Evaporation Predict Using Climate Signals and Artificial Neural Network in Dez Basin. geores. 2015; 30 (2) :261-274
URL: http://georesearch.ir/article-1-650-en.html


Volume 30, Issue 2 (2015) Back to browse issues page
فصلنامه تحقیقات جغرافیایی Geographical Researches Quarterly Journal
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