چکیده مقاله
Potential Evapotranspiration ETo is an important hydro climate variable It plays a significant role in many areas, for instance, in managing and planning for irrigation systems, rainfall runoff process, river basin yield and reservoir capacity In this study, a framework to forecast monthly ETo using the outputs of Climate Forecast System Version 2 CFS v2 model with the WNN post processing approach was proposed Since the accuracy of temperatureforecasts are usually higher than those of other climatic factors, in the current research, monthly temperature forecasts were utilized to forecast ETo First, daily ETo was calculated from observed climatic data using the much taunted FAO PM56 method for the period of 2010 to 2017 These daily ETo data were then transformed to the mean monthly In the following step, a onemonth lead time forecasted temperature data at the standard 2m height minimum, maximum and average for the same period, was extracted from the outputs of the model Finally, theforecasted temperature data by the CFS v 2 model for the next month and the calculated ETo using the observed climatic data were employed as inputs and outputs to the ANN and WNN, respectively The results showed that both ANN and WNN are able to forecast ETo for the following month with good accuracy However, it was found that the WNN was more robust Keywords: CFS v2, potential evapotranspiration, ANN, WNN, FAO PM56, Urumia Lake Basin Iran
کلیدواژهها
نویسندگان
Yashar Falamarzi
Atmospheric Science & Meteorological Research Center, Climatological Institute, Climate Modeling and Prediction Division, Iran
Morteza Pakdaman
Atmospheric Science & Meteorological Research Center, Climatological Institute, Climate Disasters and Changes Division, Iran
Zohreh Javanshiri
Atmospheric Science & Meteorological Research Center, Climatological Institute, Applied Climatology Division, Iran
Yuk Feng Huang
Department of Civil Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Selangor, Malaysia
ایمان بابائیان
Atmospheric Science & Meteorological Research Center, Climatological Institute, Climate Modeling and Prediction Division, Iran
شیوه ارجاع
Falamarzi, Yashar and Pakdaman, Morteza and Javanshiri, Zohreh and Feng Huang, Yuk and Babaeian, Iman,1399,Monthly Reference Evapotranspiration Forecast Using CFS.v2 And Wavelet Neural Network (WNN),8th National Conference on Water Resources Management of Iran,Mashhad
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