Modeling and routing of surface evaporation from the Amir Kabir reservoir using the Mann-Kendall and neural network technology

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Jahangir Mohammadhossein; SOLTANI KEYVAN; NOHEGAR AHMAD; SADATINEJAD SEYED JAVAD

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Journal: WATERSHED ENGINEERING AND MANAGEMENT Year:2019 | Volume:10 | Issue:4 Page(s): 635-644

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Title

Modeling and routing of surface evaporation from the Amir Kabir reservoir using the Mann-Kendall and neural network technology

Author(s)

Jahangir Mohammadhossein | SOLTANI KEYVAN | NOHEGAR AHMAD | SADATINEJAD SEYED JAVAD | Issue Writer Certificate

Keywords

Correlation coefficientQ1

NeuronQ1

Model accuracyQ1

Test and training dataQ2

Try and errorQ1

Abstract

Evaporation as a natural parameter due to the release of water from the upper part of mankind has always been of interest to scholars and researchers. In this study, we try to apply the artificial neural network model to estimate evaporation from the Amir Kabir dam and to evaluate the Model accuracy. In this context, 18 years data from 1997 to 2014 were used and after consecutive Try and error, the best structure for computing the amount of evaporation from the surface of the dam was selected. This structure has five Neurons in the first, fourth and second layers that showed the best result in 1000 replications. Also, statistical coefficients obtained from the analysis using artificial neural network was considered in choosing the best structure with the amount of 0. 9365 which was the highest amount among other tests and the amount of Test and training data error were 0. 0321 and 0. 0311, respectively. In addition, general trend of effective data on evaporation was determined, using Mann-Kendall test on 15 years daily data. In Mann-Kendall method, temperature changes, wind speed and precipitation graphs had no significand trend and showed-1. 69< U <1. 69. Water level among 2000 to 2014 U has exceeded from 1. 69 that shows the rising trend in this period and has decreased again after all these years. In the trend of evaporation monthly changes between 2000 and 2014 U has exceeded out of-1. 69 that shows sovereignty of negative trend in this period.

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APA: Copy

Jahangir, Mohammadhossein, SOLTANI, KEYVAN, NOHEGAR, AHMAD, & SADATINEJAD, SEYED JAVAD. (2019). Modeling and routing of surface evaporation from the Amir Kabir reservoir using the Mann-Kendall and neural network technology. WATERSHED ENGINEERING AND MANAGEMENT, 10(4 ), 635-644. SID. https://sid.ir/paper/234613/en

Vancouver: Copy

Jahangir Mohammadhossein, SOLTANI KEYVAN, NOHEGAR AHMAD, SADATINEJAD SEYED JAVAD. Modeling and routing of surface evaporation from the Amir Kabir reservoir using the Mann-Kendall and neural network technology. WATERSHED ENGINEERING AND MANAGEMENT[Internet]. 2019;10(4 ):635-644. Available from: https://sid.ir/paper/234613/en

IEEE: Copy

Mohammadhossein Jahangir, KEYVAN SOLTANI, AHMAD NOHEGAR, and SEYED JAVAD SADATINEJAD, “Modeling and routing of surface evaporation from the Amir Kabir reservoir using the Mann-Kendall and neural network technology,” WATERSHED ENGINEERING AND MANAGEMENT, vol. 10, no. 4 , pp. 635–644, 2019, [Online]. Available: https://sid.ir/paper/234613/en

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