Modeling pan evaporation using GARCH model for moderate and semi rainy climate of Iran

سال انتشار: 1393
محل انتشار: کنفرانس بین المللی توسعه پایدار، راهکارها و چالش ها با محوریت کشاورزی، منابع طبیعی، محیط زیست و گردشگری
کد COI اختصاصی: ICSDA01_0131
زبان مقاله: انگلیسی
تعداد مشاهده: 914

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نویسندگان

s.s Eslamian

Professor Department of Water Engineering, College of Agriculture, Isfahan university of Technology, Iran,

s goli

Assistant Professor Department of Statistics Isfahan university of Technology, Iran

a Shirzadian

B.s Department of Water Engineering, College of Agriculture, Isfahan university of Technology, Iran,

چکیده

In the past 50 years, many observations show that the rate of evaporation from the pans have been changing all over the world. Based on the data from 8 meteorology stations in moderate and semi rainy climates of Iran from 1990 to 2010, the autocorrelation (ACF) and partial autocorrelation (PACF) of the selected series revealed the seasonal behavior of the monthly evaporation. After the estimation of model's parameters, the residuals of the models analyzed to be time independent and the normality was checked using Portmanteau lack of fit and nonparametric tests. The ARCH and GARCH models were fitted to monthly evaporation time series of the stations. The α = 0.05 significant level is used as the significant level for the model building The results of the time series modeling showed the mainly increasing trend evaporation in majority of stations. The most important consequences of the global warming is that the air near the surface becomes drier, which would be accompanied with an increase of the evaporation from open water bodies. This estimation is useful to design irrigation scheduling and management of water supply to improve agriculture production in future. The evaporation time series models fitted to monthly evaporation of the selected stations can also be used for estimating missing evaporation values, evaporation investigating and forecasting future evaporation changes due to global climate change

کلیدواژه ها

Climate variability; Trend; Time Series; GARCH

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